Top AI Machine Learning Engineer Jobs Openings in 2025

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About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We are seeking an experienced Machine Learning Systems Engineer to join our Encodings and Tokenization team at Anthropic. This cross-functional role will be instrumental in developing and optimizing the encodings and tokenization systems used throughout our Finetuning workflows. As a bridge between our Pretraining and Finetuning teams, you'll build critical infrastructure that directly impacts how our models learn from and interpret data. Your work will be foundational to Anthropic's research progress, enabling more efficient and effective training of our AI systems while ensuring they remain reliable, interpretable, and steerable. Responsibilities Design, develop, and maintain tokenization systems used across Pretraining and Finetuning workflows Optimize encoding techniques to improve model training efficiency and performance Collaborate closely with research teams to understand their evolving needs around data representation Build infrastructure that enables researchers to experiment with novel tokenization approaches Implement systems for monitoring and debugging tokenization-related issues in the model training pipeline Create robust testing frameworks to validate tokenization systems across diverse languages and data types Identify and address bottlenecks in data processing pipelines related to tokenization Document systems thoroughly and communicate technical decisions clearly to stakeholders across teams You May Be a Good Fit If You Have significant software engineering experience with demonstrated machine learning expertise Are comfortable navigating ambiguity and developing solutions in rapidly evolving research environments Can work independently while maintaining strong collaboration with cross-functional teams Are results-oriented, with a bias towards flexibility and impact Have experience with machine learning systems, data pipelines, or ML infrastructure Are proficient in Python and familiar with modern ML development practices Have strong analytical skills and can evaluate the impact of engineering changes on research outcomes Pick up slack, even if it goes outside your job description Enjoy pair programming (we love to pair!) Care about the societal impacts of your work and are committed to developing AI responsibly Strong Candidates May Also Have Experience With Working with machine learning data processing pipelines Building or optimizing data encodings for ML applications Implementing or working with BPE, WordPiece, or other tokenization algorithms Performance optimization of ML data processing systems Multi-language tokenization challenges and solutions Research environments where engineering directly enables scientific progress Distributed systems and parallel computing for ML workflows Large language models or other transformer-based architectures (not required) Deadline to apply: None. Applications will be reviewed on a rolling basis. The expected salary range for this position is:Annual Salary:$300,000—$405,000 USDLogistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

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Your ImpactAs an AI Tutor, Computer Science Specialist, you will play a vital role in shaping how advanced AI models understand and communicate complex computing concepts. Leveraging your deep knowledge of algorithms, data structures, systems, and software engineering, you’ll evaluate and improve AI-generated content to ensure technical accuracy, conceptual clarity, and educational value. Your work will directly support the training of large language models (LLMs) used in software development, computer science education, and technical research.This is a contract remote position with variable time commitments. The services to be provided by the Contractor under this agreement are supplementary and not integral to the Handshake’s primary business operations. The Contractor’s services are distinct and separate from the core business activities of Handshake.Your RoleUse internal tools to review and refine AI-generated responses related to computer science and software engineering.Assess outputs for technical correctness, programming relevance, and clarity in areas such as algorithms, data structures, operating systems, networking, databases, and software design patterns.Curate high-quality datasets used for training and fine-tuning AI models in computing domains.Identify model blind spots, edge cases, and inconsistent or misleading explanations in computer science topics.Collaborate with cross-functional AI teams to improve content quality and knowledge alignment across technical disciplines.Your ExperiencePhD or MS in Computer Science, Software Engineering, or a closely related technical field.Alternatively, 3+ years of professional experience in software engineering, computer science research, or technical education.Strong understanding of core CS topics, including algorithms, data structures, programming paradigms, and systems fundamentals.Proficiency in at least one major programming language (e.g., Python, Java, C++, Go, Rust, JavaScript).Strong written communication skills, especially for explaining complex technical concepts clearly and concisely.Ability to critically evaluate technical content and provide detailed, constructive feedback.Comfortable working independently and navigating ambiguity in fast-evolving workflows.Bonus ExpertisePublications in peer-reviewed computer science journals or conferences.Teaching, tutoring, or curriculum development experience in computer science.Experience with competitive programming or contributions to open-source projects.Familiarity with LLMs, prompt engineering, or AI-driven educational tools.Background in human-in-the-loop feedback systems or technical annotation pipelines.Additional RequirementsAvailable to work evenings or weekends as needed.Comfortable adapting to rapidly changing workflows and AI tools.Personal device must support Windows 10 or macOS Big Sur 11.0 or later.Reliable smartphone access for secure login and multi-factor authentication.Location & Work Expectations100% RemoteNo visa sponsorship availableNot hiring in Wyoming or Illinois at this timeCompensation Range$55/hr – $100/hr We benchmark our compensation ranges against similar stage companies. Final compensation will be based on factors such as location, relevant experience, and skill alignment.

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About UsAt Harmattan AI, we are a next-generation defense prime building autonomous and scalable defense systems. Driven by rigorous engineering developments of new defense products based on recent robotics and AI developments, we are on a steep growth trajectory. If you are interested in a career in a highly technical environment, thrive on pushing boundaries, and want to achieve ambitious goals, we would love to hear from you.At Harmattan AI, we design and deploy advanced AI-powered systems for defense. Our work sits at the intersection of cutting-edge technology and national security, fast-moving, high-stakes, and deeply mission-driven.We hire selectively and work with urgency, precision, and a commitment to solving problems that matter. If you're exceptional in your field and driven by building real-world impact, we want to hear from you.Even if no listed role matches your profile, we welcome proactive applications from individuals who thrive in high-responsibility environments and bring deep expertise in areas such as:Aerospace & Robotics – GNC, autonomy, flight software, mission planningEmbedded Systems & Hardware – FPGA, real-time systems, electronicsSoftware & AI – machine learning, perception, signal processingBusiness, Strategy & Operations – program execution, partnerships, international expansionWhat we’re looking forWe value individuals who:Set a high personal bar for quality and technical excellenceTake ownership and move fast under uncertaintyPush boundaries, challenge assumptions, and deliver under pressureAre motivated by complex challenges with meaningful geopolitical stakesWhat to includeA resumeA short message telling us what you’re best at, and how you think you could contribute to our missionWe review all applications thoroughly and will reach out if there’s a potential fit.We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

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About Brain Co.Brain Co. is at the leading edge of productionizing artificial intelligence for real world problems, propelling advancements and shaping the future with pioneering work. Our mission is to ensure that the transformative powers and automation of AI are applied to real world problems in various governments where manual work is still dominant. We are seeking visionary AI/ML Engineers with experience in GenAI and ML modeling, where you will convert groundbreaking research into real-world applications that revolutionize industries, boost human creativity, and address complex challenges. About The RoleAs an AI/ML Engineer at Brain Co., you will play a crucial role in deploying state-of-the-art models to automate various real world problems in sectors such as healthcare, government and energy. Part of the role will involve turning research breakthroughs into practical solutions for various nation states. This role is your opportunity to make a significant impact by making AI technology both accessible and influential. In This Role, You Will:Innovate and Deploy: Design and deploy advanced LLM models to tackle real-world problems, particularly in automating complex, manual processes in a range of real-world verticals.Optimize and Scale: Build scalable data pipelines, optimize models for performance and accuracy, and prepare them for production. Monitor and maintain deployed models to ensure they continue delivering value across various governments worldwide.Make a Difference: Engage in projects including but not limited to optimizing the world's most advanced energy production systems, modernizing core government workflows, or improving patient outcomes in advanced public healthcare systems. Your work will directly impact how AI benefits individuals, businesses, and society at large.Engage with Leaders: interact directly with government officials in various countries and apply the first of its kind AI solutions while working alongside experienced ex. Founders, AI researchers, and software engineers to understand complex business challenges and deliver AI-powered solutions. Join a dynamic team where ideas are exchanged freely and creativity flourishes. You will be able to wear many hats: software building, product management, sales, interpersonal skills.Learn and Lead: Keep abreast of the latest developments in machine learning and AI. Participate in code reviews, share knowledge, and set an example with high-quality engineering practices. You Might Thrive In This Role If You:Hold a BSc/Master’s/PhD degree in Computer Science, Machine Learning, Data Science, or a related field.Have experience building GenAI-focused applications with the latest technologies, including but not limited to Agents, reasoning models and RAG.Have at least a high level familiarity with the architecture and operation of large language models.Have personally implemented models in common ML frameworks such as PyTorch, Jax or TensorFlow.Possess a strong foundation in data structures, algorithms, and software engineering principles.Exhibit excellent problem-solving and analytical skills, with a proactive approach to challenges.Can work collaboratively with cross-functional teams.Thrive in fast-paced environments where priorities or deadlines may compete.Are eager to own problems end-to-end and willing to acquire any necessary knowledge to get the job done.BenefitsCompetitive salary plus equityDaily lunchesCommuter benefits401(k)Medical, Dental and VisionUnlimited PTOThis is a hybrid role based out of our Dubai office.

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Your impactHandshake is building the future of human data for AI.We partner directly with top AI labs to power large language model (LLM) training and evaluation with high-quality, expert-generated data. As AI models become more sophisticated, the demand for specialized human input continues to grow—and Handshake is uniquely positioned to meet it. We power career platforms at 92% of the top U.S. universities, giving us direct access to verified expert talent across a wide range of domains.Our AI team is rapidly building a new generation of human data products—from expert annotation platforms to AI interviewers and seamless payout infrastructure—all designed to accelerate research and improve model performance.We’ve assembled a world-class team from YC, Notion, Scale, Coinbase, Palantir, and more, and we’re working directly with many of the world’s leading AI research labs. This is a unique opportunity to join a fast-growing team shaping the future of AI through better data, better tools, and better systems—for experts, by experts.We're looking for a Research Engineer to join our Handshake AI Research team, where you'll help shape what the next generation of AI models can achieve. This is a hands-on, high-impact role focused on post-training methodologies, specialized domain data verification, and creating cutting-edge LLM benchmarks that measure real-world impact.As a Research Engineer, you'll bring deep technical skill, curiosity, and rigor to every stage of the research-to-deployment pipeline—whether it's designing robust distributed infrastructure for massive experiments, writing high-performance ML code, or developing benchmarks and evaluations that define the future of AI capabilities.Location: San Francisco, CAYour roleDesign and implement post-training systems and methodologies in close partnership with research scientists and domain expertsBuild and maintain infrastructure that supports large-scale model training, specialized data processing, and benchmark evaluationDevelop robust frameworks for verifying the quality and integrity of highly specialized domain datasetsCreate next-generation LLM benchmarks that push the boundaries of model evaluation and capabilities assessmentOptimize performance across software and hardware layers to accelerate post-training experimentation and deploymentCollaborate across disciplines to ensure rigorous validation of model improvements and benchmark reliabilityYour experienceStrong Python programming skills with attention to clean, efficient, and scalable codeExperience building and operating large-scale systems for model post-training, specialized data processing, or benchmark evaluationDeep familiarity with PyTorch and modern post-training techniques (RLHF, constitutional AI, etc.)A background in applied machine learning, model evaluation, or large-scale data quality assessmentExperience with benchmark design, evaluation methodologies, and performance measurement frameworksClear communication skills and a collaborative mindset for cross-functional research teamsNice to HaveExperience optimizing deep learning models for performance (e.g., memory usage, training speed)Interest in the societal and ethical impacts of AI technologiesContributions to open-source ML infrastructure or toolsWhy Join UsThis is a rare opportunity to help define how the world’s top labs build, test, and evaluate cutting-edge AI systems. You’ll be working with a uniquely high-talent team, tapping into a network of 18 million students and 500K+ PhDs, and shaping foundational infrastructure at a critical moment in the field. If you're excited to build from first principles—and want your work to directly accelerate frontier AI—we'd love to talk.What we offerAt Handshake, we'll give you the tools to feel healthy, happy and secure.Benefits below apply to US employees in full-time positions.💰 Equity and ownership in a fast-growing company.🍼 16 Weeks of paid parental leave for birth giving parents & 10 weeks of paid parental leave for non-birth giving parents.💝 Comprehensive medical, dental, and vision policies including LGTBQ+ Coverage. We also provide resources for Mental Health Assistance, Employee Assistance Programs and counseling support.📚 Generous learning & development opportunities and an annual $2,000 stipend for you to grow your skills and career.💰 Financial coaching through Origin to help you through your financial journey.🛜 Monthly internet stipend and a brand new MacBook to allow you to do your best work.🚃 Monthly commuter stipend for you to expense your travel to the office (for office-based employees).🥗 Free lunch provided 5x a week in office.🏋️ Free gym access in San Francisco office building.🤝 Referral bonus to reward you when you bring great talent to Handshake.🧗🏼Team outings throughout the year to stay connected to each other.🏦 401k Match: Handshake offers a dollar-for-dollar match on 1% of deferred salary, up to a maximum of $1,200 per year.🏝 All full-time US-based Handshakers are eligible for our flexible time off policy to get out and see the world. In addition, we offer 13 standardized holidays, and 2 additional days of flexible holiday time off. Lastly, we have a Winter #ShakeBreak, a one-week period of Collective Time Off.💻 Handshake offers $500 home office stipend for you to spend during your first 3 months to create a productive and comfortable workspace at home.🍼 Family support: Parental leave coaching and support provided by Parentaly. We partner with Maven Clinic to provide a lifetime coverage up to $15K for expenses related to fertility and family forming!💰 Lifestyle Savings Account: We offer you an annual stipend of $500 to use for purchases such as fitness classes, gym memberships, work-from-home setup, and more.Looking for more? Explore our mission, values and comprehensive US benefits at joinhandshake.com/careers.Handshake is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or reasonable accommodation, please let your recruiter know during initial communications.

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Who we are:Our mission is to make the internet safer and more enjoyable for everyone. We combine state of the art AI technology and human judgment for best in class content detection, harm mitigation and safety monitoring. We are a VC-backed startup, founded by senior Google, Youtube, TikTok and Reddit executives, working with some of the world’s largest online platforms, and fast-moving startups. If you are looking for an opportunity to apply AI technology to real-world business use cases at a significant scale, and an opportunity to shape the future of how we can safely enjoy user generated online content, we’d love to hear from you.What you’ll do: As an Engineering Manager for our AI/LLM team, you will lead a group of talented engineers focused on the development and deployment of large language model (LLM) - based systems for content understanding and moderation. This is a hybrid role combining people leadership and individual technical contribution. You will help shape our technical vision, support infrastructure development, guide product alignment, and play a key part in delivering robust AI solutions to our partners.In addition to managing the team’s performance and growth, you will actively contribute to architecture, experimentation, and implementation - especially where AI systems intersect with production deployment and real-world evaluation.Key Responsibilities:Manage and mentor a high-performing team of AI Engineers working on LLM-driven content labeling and moderation systems.Design, build, and evaluate scalable training and inference infrastructure for LLMs and other AI models.Partner closely with product, engineering, and policy teams to align technical solutions with customer needs and strategic goals.Contribute to codebases by reviewing critical PRs, building prototypes, and resolving production issues.Foster a strong engineering culture centered on quality, performance, reliability, and safety.What we’re looking for:Engineering management experience, preferably in AI or ML-focused teams.Demonstrated experience delivering LLM-based solutions to production, ideally in content moderation, NLP, or safety-related domains.Proficiency in Python; strong background in cloud-based deployment (especially AWS) and CI/CD processes.Deep familiarity and track record of being hands on with model evaluation, including handling imbalanced datasets and defining success metrics for classification models.Why Join Us?Work with a group of renown industry leaders in AI and Online Safety to shape the future of the industry.Ample opportunity and support for growth, as a technical individual contributor, or manager.Apply AI technology to real-world business use cases at a significant scale, with blue chip customersCompetitive compensation, comprehensive benefits, and hybrid in-office policy.Pay range is specific to the U.S. – Bay Area; compensation may differ by region.The pay range for this role is: 180,000.00 - 250,000.00 USD per year (Palo Alto)

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Job Title: Lead Machine Learning Engineer (Computer Vision) Location: Washington, DC (Hybrid – 1 day/week in office) Note: Applicants must possess a minimum of 7 years of hands-on experience in production (non-research focused) environments, excluding internships, to be considered for this position. Prior leadership or mentorship experience is strongly preferred.Company Overview Each year, over 4 million people die from complications following surgery. At the Surgical Data Science Collective (SDSC), a mission-driven nonprofit, we’re changing that. We harness the power of machine learning and computer vision to analyze surgical video and provide actionable feedback to improve surgical technique and outcomes. Our vision is to make surgery safer and smarter through technological innovation, and we’re looking for exceptional talent to help us do it.Position SummaryWe are seeking a Lead Machine Learning Engineer with deep expertise in computer vision and deep learning, and a proven ability to drive complex projects from ideation to deployment. This is a hands-on leadership role, combining technical excellence with strategic thinking and team collaboration. You’ll help define our technical roadmap, mentor engineers, and lead the development of algorithms and systems that analyze surgical video at scale.You’ll work closely with our Director of Machine Learning and cross-functional teams of researchers, engineers, and clinical partners to turn real-world surgical video into breakthrough insight and feedback tools. You'll also play a critical role in translating research and experimentation into production-ready systems, helping bring ML models into real-world use as core features of our surgical analytics platform.Key ResponsibilitiesLead the design and development of state-of-the-art computer vision and ML algorithms focused on surgical video analysis.Mentor and guide a small team of engineers while contributing directly to code and system architecture.Architect and optimize data pipelines, model training workflows, and inference systems for high-volume video data.Collaborate with researchers and clinicians to translate user needs and scientific advances into robust technical solutions.Own the technical design and implementation of CV/ML systems, from prototype to production deployment.Lead efforts to productize ML models, ensuring scalability, performance, and seamless integration with core product features.Continuously evaluate and integrate emerging technologies, models (e.g., ViTs), and tools to elevate SDSC’s capabilities.Contribute to and review technical documentation and help establish engineering best practices across the team.Minimum Qualifications7+ years of professional experience in machine learning and computer vision, including production-level model deployment.Proven leadership experience — team mentorship, technical lead roles, or ownership of complex projects.Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related technical field.Deep experience with Python, OpenCV, and deep learning frameworks such as PyTorch, TensorFlow, or Keras.Strong understanding of modern neural network architectures (CNNs, RNNs, LSTMs, ViTs) for image and video analysis.Demonstrated experience bringing ML models into production as part of a product or system, not just in research or prototype phases.Hands-on experience with MLOps tools like ClearML and Weights & Biases, and cloud platforms such as AWS (SageMaker, Lambda).Experience designing scalable CV/ML pipelines, managing large datasets, and optimizing model performance.Familiarity with modern software development practices (version control, CI/CD, testing, containerization, etc.).Nice to HavesExperience with Vision Transformers (ViTs) or multimodal learning systems.Background in medical imaging or working in regulated healthcare environments.Prior experience at startups or in fast-paced, early-stage product environments.Exposure to video compression, real-time streaming pipelines, or edge deployment.Why Join Us?Join a mission-driven nonprofit dedicated to making surgery safer on a global scale.Work on challenging, high-impact ML problems with real clinical relevance.Enjoy competitive salary, 401(k), health insurance, and flexible work arrangements.Be part of a collaborative, creative, and inclusive environment where your contributions matter.About us: The Surgical Data Science Collective (SDSC) is a nonprofit on a mission to unlock the power of surgical data. We bring together surgeons, scientists, and engineers to turn surgical videos into searchable, data-rich tools. Using AI, we help uncover insights that improve technique, sharpen decision-making, and elevate patient care. From smarter metrics to secure video libraries, we give surgical teams the tools to ask better questions—and find better answers. Because when surgeons get better, patients do too.

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About Mistral At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. We are a dynamic, collaborative team passionate about AI and its potential to transform society.Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers. About The Job Mistral AI is seeking a Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges. The Applied AI Engineer will be an integral part of our Applied AI Engineering team, which is dedicated to driving the successful deployment of Mistral AI products. They will work hand-in-hand with customers from the pre-sale stage to post-implementation, ensuring our solutions meet and exceed client expectations.  In this role, you’ll manage daily customer relations involving multiple stakeholders (CEO/CTO, data scientists, and software engineers) and function as a key resource in externalising our research in production settings. What you will do • You’ll be responsible for onboarding customers on our products and APIs, providing guidance on prompting, evaluation, and fine-tuning, and ensuring the best production integration with back-end and front-end interfaces. • You’ll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation. • You’ll individually help deploy into production use cases with a considerable business impact across various industries. • You’ll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases our open source codebases for tasks such as inference and fine-tuning.• You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders. • Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers’ feedback   About you • You are fluent in English• You hold a PhD / master in AI / data science.• You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products• You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases• You have deep understanding of concepts and algorithms underlying machine learning and LLMs• You're experienced with building and deploying LLMs or NLP applications• You have proven experience in AI or machine learning product implementation with APIs, back-end and front-end interfaces.• You have strong technical coding skills in Python• You have experience with deep learning with Pytorch• You have experience with agents framework such as Langchain, vector DBs• You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences Ideally you have: • Contributed to open-source projects in particular in the space of LLMs• Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager Benefits We have local offices in Luxembourg, Paris, Marseille, London and Singapore. France 💰 Competitive cash salary and equity🥕 Food : Daily lunch vouchers🥎 Sport : Monthly contribution to a Gympass subscription 🚴 Transportation : Monthly contribution to a mobility pass🧑‍⚕️ Health : Full health insurance for you and your family🍼 Parental : Generous parental leave policy🌎 Visa sponsorship UK 💰 Competitive cash salary and equity🚑 Insurance🚴 Transportation: Reimburse office parking charges, or 90GBP/month for public transport🥎 Sport: 90GBP/month reimbursement for gym membership🥕 Meal voucher: £200 monthly allowance for its meals💰 Pension plan: SmartPension (percentages are 5% Employee & 3% Employer)

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Austin, TX  | Manhattan, NYC | Hybrid (Minimum 4 days in office)  |  Full Time  |  https://kizen.com About Us At Kizen, we’re engineering a more humane future where AI drives universal healthcare, more impactful work, world-class education, exceptional customer experiences, and — overall — a more fulfilling human experience. Kizen is on a mission to give every team member an AI Assistant - turning every company into an AI-company, every worker into an AI-Enhanced Worker, and every Process into an AI-optimized, continuously improving process. Kizen is the first GenAI enterprise application builder. Businesses of any size, within any industry can build AI assistants for complex jobs across healthcare, finance, and HR and modern enterprise applications - like CRMs, Workflow Automation, Real Time Dashboards, and Secure Portals in minutes and perfect them in an afternoon. Kizen helps teams systematically improve processes and business outcomes with data-driven insights and powerful automation with access to all the latest AI models. About the Role Shape the Future of AI at Kizen Are you ready to push the boundaries of what's possible with AI and backend systems? At Kizen, we're engineering intelligent systems that combine cutting-edge AI with robust backend architecture to revolutionize healthcare, redefine work-life balance, transform education, and elevate customer experiences. Our mission is to create technology that doesn't just work – it transforms how businesses operate. As we rapidly expand, we're seeking exceptional engineers who excel in both AI development and backend systems. This is your opportunity to be part of something transformative – to architect and build systems that set new benchmarks for what technology can achieve across industries. At Kizen, you'll join a brilliant, fun team tackling challenges that matter. We offer: The opportunity to work on groundbreaking AI technologies with real-world impact A startup culture that values innovation, ownership, and rapid iteration Regular opportunities to present your technical solutions to company leadership A supportive environment for professional growth and learning We're looking for a Principal AI Engineer to provide strategic feedback and direction for our engineering team as we bring our next-generation platform to the world. In this position, you'll architect, plan, and build sophisticated AI systems with collaborators seamlessly integrating with our backend infrastructure, focusing on generative AI, retrieval-augmented generation (RAG), and multi-agent architectures. Key Responsibilities Lead the design and implementation of production-ready RAG systems that integrate seamlessly with our backend infrastructure using Django, Kafka, PostgreSQL, and Clickhouse Architect multi-agent AI systems that operate effectively within our platform's constraints and understand business value implications. Drive product strategy by providing accurate work estimations and technical roadmaps with minimal supervision. Design and implement sophisticated vector search solutions, including graph-based RAG systems Architect and build highly scalable LLM-powered systems that can handle enterprise-level workloads Lead LLM fine-tuning initiatives to customize models for specific business domains and use cases Design and implement user feedback systems to collect, analyze, and incorporate insights for continuous improvement Optimize LLM performance, cost, and reliability in production environments Establish MLOps best practices using platforms like Langfuse or LiteLLM to ensure robust model monitoring and evaluation Mentor and develop junior engineers in AI/ML best practices Collaborate with cross-functional teams to translate business requirements into technical solutions Lead system architecture decisions and technical direction for AI initiatives Evaluate emerging AI technologies for potential adoption Experience Required Qualifications Education and Experience Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field 8+ years of backend engineering experience with Django, Kafka, and PostgreSQL 4+ years of hands-on experience building and deploying machine learning systems Proven track record of implementing production RAG systems at scale  Strong experience in product management, including work estimation and roadmap planning Experience building solutions at scale with large enterprise data in healthcare, finance, or banking sectors. Technical Expertise Expert-level Python development skills with Django experience Deep understanding of distributed systems and message queuing using message broker systems (e.g., Kafka) Advanced PostgreSQL knowledge, including optimization for AI workloads Experience building and optimizing retrieval-augmented generation (RAG) systems Experience architecting and implementing multi-agent AI systems Knowledge of deep learning frameworks (PyTorch or TensorFlow) and NLP, particularly transformer architectures Experience with cloud platforms (AWS preferred) and containerization (Docker, Kubernetes) Experience building solutions using pre-trained LLMs (OpenAI, Claude, Llama, etc.) Strong background in MLOps practices and tools, including platforms like Langfuse or LiteLLM Proficiency in writing clean, well-documented code and troubleshooting complex issues Experience in testing and validating products and communicating results with stakeholders ML/AI Experience Experience applying graph algorithms to machine learning problems Strong experience with modern NLP techniques and transformer architectures Knowledge of evaluation metrics for NLP system performance Solid foundation in probability theory and statistical inference Experience with statistical modeling and hypothesis testing Understanding of sampling methods and experimental design LLM Systems Expertise Proven experience designing and implementing scalable LLM-powered systems in production environments Deep understanding of LLM orchestration and optimization techniques for high-throughput applications Experience with prompt engineering, fine-tuning, and context window management for optimal LLM performance Demonstrated expertise in LLM fine-tuning methodologies, including RLHF, PEFT, and LoRA techniques Experience building data collection pipelines for LLM training and fine-tuning Knowledge of efficient usage strategies, cost optimization for LLM API consumption, and performance optimization of large-scale deployments. Experience implementing LLM caching mechanisms and vector store optimizations Expertise in designing fault-tolerant LLM architectures with appropriate fallback mechanisms Understanding of techniques to reduce latency in LLM-powered applications Knowledge of strategies for handling data privacy and security in LLM applications User Feedback and System Improvement Knowledge of model monitoring and evaluation techniques Experience designing and implementing robust user feedback collection systems for AI applications Knowledge of feedback aggregation and analysis techniques to identify patterns and improvement areas Experience building systems that leverage user feedback for continuous LLM improvement Understanding of human-in-the-loop approaches for refining AI system outputs Experience with A/B testing frameworks to evaluate AI system changes Ability to translate user feedback into actionable model improvements Experience implementing evaluation frameworks to measure AI system quality and performance Professional Skills Demonstrated ability to lead technical initiatives and architectural decisions Experience managing technical product roadmaps and providing accurate work estimations Strong problem-solving skills and ability to work independently on complex projects Strategic thinking ability to balance immediate solutions with long-term scalability Excellent collaboration skills when working with cross-functional teams Excellent written and verbal communication skills in English Driven, self-motivated, adaptable, empathetic, energetic, and detail-oriented Preferred Qualifications Experience with graph-based RAG systems Contributions to open-source projects in backend or AI domains Experience with streaming data processing at scale Deep interest in emerging AI technologies and their practical applications Strong mentoring capabilities to guide and develop team members Ability to work in our Los Angeles or Austin office Why Kizen We’re a fast-growing company that values innovation, growth, and continuous improvement. By joining Kizen, you’ll play a pivotal role in shaping the future of the company while enjoying a supportive, dynamic, and collaborative workplace. You’ll have opportunities for professional development, impact, and career advancement. What We Offer Hybrid Work Model Career Growth Opportunities Engaging Work Culture Top-Tier Compensation Equity Package Healthcare Coverage Professional Development Stipends PTO  Kizen is proud to be an equal-opportunity employer. We are committed to building a diverse and inclusive culture that celebrates authenticity to win as one. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, citizenship or immigration status, or any other legally protected characteristics. At Kizen, we fully comply with the Americans with Disabilities Act (ADA). We are dedicated to embracing challenges and creating an accessible, inclusive workplace for all individuals.  The base salary range for this position is $250,000-$350,000. However, base pay offered may vary depending on job-related knowledge, skills, and experience. In addition to base salary, we also offer generous equity and benefits packages. If you’re excited about creating impact experiences and contributing to a fast-paced, people-focused team, we’d love to meet you! OTE - $312,000-$412,000KCompensation Range$250,000—$400,000 USD

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Shape the Future of AI At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially. About Labelbox We're the only company offering three integrated solutions for frontier AI development: Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale Frontier Data Labeling Service: Specialized data labeling through Aligner, leveraging subject matter experts for next-generation AI models Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling Why Join Us High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions. Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence. Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution. Continuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI. Clear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics. Role Overview Labelbox is seeking Subject Matter Experts (SMEs) to support high-impact AI data projects across a range of specialized domains, including Math, STEM, Programming, and Internationalization (i18n). As an SME, you’ll bring deep domain knowledge to help shape data labeling workflows, ensure quality, and guide contributor success. This is a contract-based role, deployed per project depending on expertise needs. Employment Type: Project-based, paid hourly Your Impact Design project structures and labeling workflows tailored to domain-specific goals Develop clear contributor guidelines and quality assurance frameworks Define ideal contributor profiles and task acceptance criteria Collaborate with internal teams to ensure subject matter accuracy and relevance What You Bring Proven expertise in one or more relevant domains (e.g., Math, Programming, i18n, etc.) Experience designing or reviewing data workflows, educational content, or technical documentation Strong communication and organizational skills Bonus Points Prior experience with data labeling, ML/AI, or evaluation projects Alignerr Services at Labelbox As part of the Alignerr Services team, you'll lead implementation of customer projects and manage our elite network of AI experts who deliver high-quality human feedback crucial for AI advancement. Your team will oversee 250,000+ monthly hours of specialized work across RLHF, complex reasoning, and multimodal AI projects, resulting in quality improvements for Frontier AI Labs. You'll leverage our AI-powered talent acquisition system and exclusive access to 16M+ specialized professionals to rapidly build and deploy expert teams that help customers like Google and ElevenLabs achieve breakthrough AI capabilities through precisely aligned human data—directly contributing to the critical human element in advancing artificial intelligence. #LI-RemoteLife at Labelbox Location: Join our dedicated tech hubs in San Francisco or Wrocław, Poland Work Style: Hybrid model with 2 days per week in office, combining collaboration and flexibility Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making Growth: Career advancement opportunities directly tied to your impact Vision: Be part of building the foundation for humanity's most transformative technology Our Vision We believe data will remain crucial in achieving artificial general intelligence. As AI models become more sophisticated, the need for high-quality, specialized training data will only grow. Join us in developing new products and services that enable the next generation of AI breakthroughs. Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs. Your Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice. Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.

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Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.Join us on our mission and shape the future!Why this role?Agentic LLM systems are being deployed widely across enterprise companies including through Cohere’s North platform. The Next Generation Agents team is exploring the horizon of modeling techniques to improve agent capabilities (e.g., deep-research, learning-from-experience, continual learning, and memory). We work in an empirical-research-driven manner to develop production solutions. Much of the work is based on improving beyond the current state-of-the-art in a setting where we know this will bring value to our customers.As a part of this team, you will help drive exploration and development of agentic techniques. You will have the opportunity to build the models that power our agentic solutions. This includes developing data-generation techniques for post-training (SFT and RL*) Cohere’s models.Please Note: We have offices in London, Toronto, San Francisco, and New York, but we also embrace being remote-friendly! There are no restrictions on where you can be located for this role.As a Member of Technical Staff for Next Generation Agents you will:Design and develop novel agentic solutionsImprove upon SOTA on hard agentic tasksResearch the next-generation of on-line learning-from-experience self-improvementWork with partner teams (Reasoning, Post-training, Pre-training, etc.) to improve performance of agentic systemWork with an amazing team of researchers and engineers pushing the boundariesYou may be a good fit if you have:Strong software engineering skillsProficiency in Python and have some experience with ML-related code (e.g., pytorch, numpy, etc.)Experience with LLMs and agentic frameworksExperience with post-training LLMs (SFT, PEFT, or RL*)Experience with building synthetic data generation pipelinesIf some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! If you want to work really hard on a glorious mission with teammates that want the same thing, Cohere is the place for you.We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.Full-Time Employees at Cohere enjoy these Perks:🤝 An open and inclusive culture and work environment 🧑‍💻 Work closely with a team on the cutting edge of AI research 🍽 Weekly lunch stipend, in-office lunches & snacks🦷 Full health and dental benefits, including a separate budget to take care of your mental health 🐣 100% Parental Leave top-up for 6 months for employees based in Canada, the US, and the UK🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement🏙 Remote-flexible, offices in Toronto, New York, San Francisco and London and co-working stipend✈️ 6 weeks of vacationNote: This post is co-authored by both Cohere humans and Cohere technology.

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Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.Join us on our mission and shape the future!Why this role?As a Machine Learning Engineer specializing in pretraining data, you will play a pivotal role in developing the data pipeline that underpins Cohere’s advanced language models. Your responsibilities will encompass the end-to-end management of training data, including ingestion, cleaning, filtering, and optimization, as well as data modeling to ensure datasets are structured and formatted for optimal model performance. You will work with diverse data sources—such as web data, code data, multilingual corpora, and synthetic data—to ensure their quality, diversity, and reliability.In this role, you will design and implement scalable, robust pipelines for data processing, conduct data ablations to evaluate quality, and experiment with data mixtures to enhance model performance. By combining research and engineering, you will bridge the gap between raw data and cutting-edge AI models, directly contributing to improvements in critical training metrics like throughput and accelerator utilization.Your work will be essential to Cohere’s mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a meaningful impact.Please Note: We have offices in London, Toronto, San Francisco, New York but also embrace being remote-friendly! There are no restrictions on where you can be located for this role.As a Machine Learning Engineer (Pre-Training Data), you will:Design and build scalable data pipelines to ingest, clean, filter, and optimize diverse datasets, including web data, code data, multilingual corpora, and synthetic data.Conduct data ablations to assess data quality and experiment with data mixtures to enhance model performance.Develop robust data modeling techniques to ensure datasets are structured and formatted for optimal training efficiency.Research and implement innovative data curation methods, leveraging Cohere’s infrastructure to drive advancements in natural language processing.Collaborate with cross-functional teams, including researchers and engineers, to ensure data pipelines meet the demands of cutting-edge language models.You may be a good fit if you have:Strong software engineering skills, with proficiency in Python and experience building data pipelines.Familiarity with data processing frameworks such as Apache Spark, Apache Beam, Pandas, or similar tools.Experience working with large-scale datasets, including web data, code data, and multilingual corpora.Knowledge of data quality assessment techniques and experimentation with data mixtures.A passion for bridging research and engineering to solve complex data-related challenges in AI model training.Bonus: paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! If you want to work really hard on a glorious mission with teammates that want the same thing, Cohere is the place for you.We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.Full-Time Employees at Cohere enjoy these Perks:🤝 An open and inclusive culture and work environment 🧑‍💻 Work closely with a team on the cutting edge of AI research 🍽 Weekly lunch stipend, in-office lunches & snacks🦷 Full health and dental benefits, including a separate budget to take care of your mental health 🐣 100% Parental Leave top-up for 6 months for employees based in Canada, the US, and the UK🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement🏙 Remote-flexible, offices in Toronto, New York, San Francisco and London and co-working stipend✈️ 6 weeks of vacationNote: This post is co-authored by both Cohere humans and Cohere technology.

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🚀 About Us We’re StackBlitz! We’re the team that brought you WebContainers, the first-of-its-kind technology that made it possible to run Node.js right inside your browser. That breakthrough kicked off our journey in 2019, and it’s what powers the blazing-fast online IDE used by over 1 million developers every month. But we didn’t stop there. We doubled down on everything we learned and built Bolt.new — the fastest way to go from idea to production without writing traditional code. It’s a next-gen, AI-powered app builder that helps you create, edit, and deploy full-stack web and mobile apps instantly, right in your browser. No installs. No setup. Just smart automation and instant dev environments that let you move at the speed of thought. We’re a fully remote team, globally distributed, deeply collaborative, and seriously passionate about building the future of software development. This is your chance to join a small team with a big vision. If you love shipping fast, solving real problems, and pushing the boundaries of what’s possible, we’d love to meet you. ✨ About This Opportunity Join us on the forefront of AI-powered development as we revolutionize how software gets built. As a Senior Applied Engineer, you will be the driving force behind our AI agents that transform natural language into production ready applications. You will work with state-of-the art LLMs, pioneering new ways to make AI understand, reason about, and generate complex full-stack applications. This isn’t just about integrating APIs, instead it’s about pushing the boundaries of what AI can do to empower our users to build stunning apps. As part of this role, you will work in an interesting problem space and tackle challenges like maintaining context across large codebases, orchestrating multi-step workflows that feel intuitive to users, and making sure our AI agents can handle everything from simple UI changes to complex architectural decisions. Your work will directly impact how millions of users bring their ideas to life. This is a unique opportunity to shape the future of AI-assisted development in a fully remote, globally distributed team that ships fast and thinks big. If you are passionate about making AI more capable, reliable, and accessible to builders everywhere, this role offers the perfect opportunity to innovate and see your work deployed at scale. 🛠️ How You'll Contribute  Develop AI Agents: Design and implement AI agent features and extend existing agents with new capabilities. This includes managing the agent’s context (using techniques like sub-agents, retrieval based context management, sliding context windows, etc.) so it can handle long conversations or large knowledge and code bases efficiently. Integrate Multiple LLM Providers: Leverage models from providers such as OpenAI (GPT series), Anthropic (Claude), and Google (Gemini). Quantitatively evaluate and choose the best model for a given task, and incorporate new model features or improvements (often by beta-testing new releases and assessing their strengths). Tool Use and Workflow Orchestration: Enable the AI agent to call external tools and APIs safely and effectively. Implement structured approaches to allow the agent to perform actions like web searches, database queries, fetch additional information, or other domain-specific operations. Utilize frameworks such as Vercel’s AI SDK, LangGraph and others for building multi-step AI workflows. Cross-Functional Collaboration: Work closely with your peer software engineers and product managers to embed AI capabilities into the product lifecycle. Ensure that AI-driven features are production-ready, meaning they are efficient, maintainable, and well-monitored in deployment. Continuous Improvement and Evaluation: Stay up-to-date with the latest research in NLP and LLMs, and experiment with novel techniques (e.g. new prompting strategies, context handling methods, model fine-tuning opportunities). Continuously evaluate the AI system’s performance using systematic tests and user feedback, and iterate on prompts, agents and workflows to improve output quality and reliability (for example, by developing automated LLM evaluation benchmarks). 💡 Qualifications TypeScript Proficiency: Strong proficiency in TypeScript is essential, as it's our primary programming language for building AI agent systems and integrations. LLM Experience: Hands-on experience working with Large Language Models (LLMs) and understanding their capabilities and limitations. Proven experience building applications or systems powered by LLMs. Prompt Engineering: Deep understanding of prompt engineering best practices to guide LLM behavior. Able to craft, refine, and optimize prompts for different tasks and models. Software Engineering Skills: Solid software engineering fundamentals with experience in building production-ready systems. Problem-Solving: Strong analytical and problem-solving skills with the ability to debug complex AI behaviors. Strong verbal and written English communication skills are required, as this role involves frequent collaboration with team members, stakeholders, and customers where English is the primary working language. 🎯 Bonus Points  DSPy Framework: Familiarity with DSPy (Declarative Self-improving Python) for building modular AI systems and optimizing prompts programmatically. Machine Learning Background: Understanding of ML fundamentals and experience with model evaluation metrics. Open Source Contributions: Experience contributing to or maintaining open-source AI/ML projects. Research Background: Experience reading and implementing techniques from AI/ML research papers. 📌 A Few Notes You do not need a college degree to apply You do not need to be located in the U.S. — we’re remote-friendly You do not need to meet every qualification listed above

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About Freight Hero:The freight brokerage industry has exploded in recent years, growing from a mere 6% to over 20% of US truck freight in just a decade, now valued at $21 billion. Freight brokers typically allocate up to 90% of their time to operational back-office tasks, leaving only 10% for revenue-generating activities (depending on the business model). By combining AI with human oversight, we can streamline these back-office processes, driving significant operational efficiencies. The industry's profit margins have recently contracted from 20% to 5%, underscoring the critical need for cost reduction. We believe that the perfect storm of industry challenges and AI maturity presents a venture scale opportunity to revolutionize the freight brokerage sector and the broader freight/supply chain industry. Freight Hero is funded and supported by AI Fund based in Palo Alto, California. AI Fund is a team of diligent innovators who build great companies that move humanity forward by accelerating the adoption of AI. Founded by Dr. Andrew Ng, AI Fund is a startup studio focused on resolving problems to move the world forward. We build new AI companies to bridge AI technology and critical applications. Just as electricity transformed numerous industries, AI and AI Fund are poised to do the same.  What We Seek:We are looking for a AI Voice Engineer to lead the development and evolution of Freight Hero’s voice automation capabilities. You will work directly with the CEO to design a strategic roadmap for integrating voice AI into our platform—empowering human agents, automating communication-heavy workflows, and enhancing operational efficiency across the freight brokerage lifecycle. As the owner of our voice AI stack, you will make critical architectural decisions, experiment with cutting-edge tools, and iteratively improve our agentic voice systems for real-world logistics execution. What You Will Be Doing:Own the Voice AI Stack – Lead architecture, development, and continual refinement of Freight Hero’s voice AI capabilities, including speech recognition, synthesis, and real-time dialogue management tailored to freight operations.Define the Strategic Vision – Establish the long-term roadmap for how voice AI can augment or automate broker workflows, from phone-based load confirmations to automated check calls and appointment scheduling.Build Agentic Voice Workflows – Design multi-turn, task-oriented voice agents using LLMs, fine-tuned models, and open-source ASR/TTS systems to handle high-volume interactions with shippers, carriers, and internal teams.Prototype, Validate, and Iterate – Rapidly develop MVPs, conduct real-world pilots, gather feedback, and fine-tune models and flows for naturalness, reliability, and compliance with industry norms.Optimize for Human-in-the-Loop Performance– Design voice workflows that integrate seamlessly with Freight Hero’s augmented ops team, empowering human agents while offloading repetitive voice tasks.Integrate with the Freight Ecosystem – Ensure your voice systems communicate effectively with TMS platforms, VOIP systems, CRMs, and broker ops tools, creating a seamless data and workflow layer.Build for Scale and Resilience – Architect scalable, cloud-native infrastructure that can handle concurrent voice sessions, asynchronous callbacks, and error recovery in real time.Collaborate Cross-Functionally – Work alongside ops, product, and engineering to align voice AI capabilities with business goals, SLA requirements, and user experience priorities.Stay Ahead of the Curve – Constantly evaluate advancements in speech AI, LLM tooling, and telephony infrastructure to keep Freight Hero on the cutting edge. What You Must Bring:English Proficiency- Strong written and verbal English communication skills required.LLM & Agentic Workflow Experience – Deep understanding of agentic workflow orchestration, prompt engineering, memory handling, and multi-turn conversation design using open-source or commercial stacks.Product Ownership Mindset – Ability to define what to build and why, balancing technical feasibility with operational impact and end-user delight.Startup Grit – Experience building from scratch in early-stage or high-velocity environments; you’re comfortable wearing multiple hats and moving fast.System Design & Infrastructure – Proficient in designing scalable voice systems that integrate securely with cloud platforms, telephony APIs (e.g. Twilio, Aircall), and internal ops tools.Human-Centric Automation – Passion for blending AI with human judgment—designing systems that enhance rather than replace frontline workers.Cross-Functional Collaboration – Strong communication skills and a bias toward action when aligning with business stakeholders and operations teams. Nice To Haves Include:AI Voice Expertise- Hands-on experience with ASR (e.g. Whisper, Deepgram), TTS (e.g. ElevenLabs, Azure), and building production-grade voicebots or virtual agents.Freight/Logistics Domain Familiarity (Nice to Have)  – Prior experience or demonstrated interest in freight, logistics, or back-office automation.

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Get to Know UsHorizon3.ai is a fast-growing, remote cybersecurity company dedicated to the mission of enabling organizations to proactively find, fix, and verify exploitable attack vectors before criminals can exploit them. Our flagship product, the NodeZero™ platform, delivers production-safe autonomous pentests and other key assessment operations that scale across the largest internal, external, cloud, and hybrid cloud environments. NodeZero has been adopted by organizations of all sizes, from small educational institutions to government agencies and Global 100 enterprises. It is used by ITOps/SecOps teams, consulting pentesters, and MSSPs and MSPs.We are a fusion of former U.S. Special Operations cyber operators, startup engineers, and formerly frustrated cybersecurity practitioners. We're committed to helping solve our common security problems: ineffective security tools, false positives resulting in alert fatigue, blind spots, “checkbox” security culture, cybersecurity skills shortage, and the long lead time and expense of hiring outside consultants. Collectively, we are a team of learn-it-alls, committed to a culture of respect, collaboration, ownership, and results.What We’re Looking ForWe’re looking for a Research Staff Member (Applied AI) to join our growing team of world-class engineers and security researchers in the San Francisco Bay Area. This is a senior/principal-level role for someone passionate about building real-world AI systems that can reason, act, and scale in adversarial environments.As a Research Staff Member (RSM) at Horizon3 focused on applied AI, you’ll turn cutting-edge research into real-world impact. Your mission: develop, prototype, and productionize AI systems that enhance our autonomous pentesting platform—powering reasoning, decision-making, and security insights at scale. You’ll work on everything from agentic workflows and LLM reasoning to reinforcement learning and graph algorithms, bridging the gap between theory and battlefield-tested cyber capabilities. This is where deep research meets operational relevance.Essential FunctionsDesign, prototype, and deploy AI-driven features that power autonomous offensive security operationsLead the development of agentic AI systems capable of planning and executing multi-step cyber operationsExplore and implement reinforcement learning, graph algorithms, and LLM-based reasoning in high-stakes, adversarial contextsTranslate academic research and new AI advances into production-ready capabilities within our platformCollaborate with engineering and security teams to integrate AI models into scalable, high-performance systemsConduct novel research with a focus on operational viability and performanceContribute to a culture of technical excellence through code reviews, technical mentorship, and knowledge sharingPresent and publish research findings internally and externally, where appropriate QualificationsPhD or MS (with equivalent experience) in AI, Computer Science, or a related field Strong publication or patent record in areas such as large language models, reinforcement learning, agentic AI, or graph-based learningProven experience applying modern AI research to real-world systemsFluency with modern AI tooling (e.g., PyTorch, Hugging Face, LangChain, OpenAI APIs)Strong programming skills in Python and familiarity with production-level ML/AI systemsDeep understanding of LLM-based architectures, fine-tuning techniques, and prompt engineeringExperience working with structured knowledge (e.g., graphs, knowledge bases, ontologies)Familiarity with adversarial ML, secure AI development, or cybersecurity applications of AI is a plus Desired/Nice to HaveWhile not required, any of the following would elevate your application:Experience in autonomous agents, multi-agent systems, or reinforcement learning in adversarial settingsPrevious work integrating AI into offensive or defensive security toolingFamiliarity with attack graph generation, pathfinding, or decision planning under uncertaintyContributions to open-source AI or cybersecurity projectsParticipation in red teaming or AI-based simulation environmentsUnderstanding of ML observability, model robustness, and bias mitigation ExpectationsOperate with a “hacker mindset” and scientific curiosityThrive in ambiguous problem spaces and take initiative to explore and drive resultsCommunicate clearly with both technical and non-technical audiencesCollaborate effectively in cross-functional teamsPrioritize impact and execution without sacrificing rigorPerks of Horizon3.aiInclusive Team: We value diversity and promote an inclusive culture where everyone can thrive.Growth Opportunities: Be part of a dynamic and growing team with numerous career development opportunities.Innovative Culture: Work in a collaborative environment that encourages creativity and out-of-the-box thinking.Remote Work: We are a 100% remote company. Enjoy the convenience and work-life balance that comes with remote work.Competitive Compensation: We offer competitive salary and benefits, including health, vision & dental care for you and your family, a flexible vacation policy, and generous parental leave. You Belong HereHorizon3 is not just an equal opportunity employer—we are a community that values diversity, equity, and inclusion as fundamental principles of our culture and success. We are dedicated to fostering a workplace where everyone feels welcome and respected, regardless of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, or any other legally protected status by law.Our commitment to diversity and inclusion means we strive to attract, develop, and retain a workforce that reflects the varied communities we serve. We believe that diverse perspectives drive innovation and strengthen our ability to create cutting-edge cybersecurity solutions. At Horizon3, every team member is valued and supported in an environment that encourages personal and professional growth.We welcome candidates from all backgrounds and experiences, and we encourage all qualified individuals to apply. Come be a part of Horizon3, where your unique contributions are recognized, and your potential is limitless.Other DutiesPlease note this job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee. Duties, responsibilities, and activities may change at any time with or without notice.. 

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About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are seeking a Machine Learning Infrastructure Engineer to join our Safeguards organization, where you'll build and scale the critical infrastructure that powers our AI safety systems. You'll work at the intersection of machine learning, large-scale distributed systems, and AI safety, developing the platforms and tools that enable our safeguards to operate reliably at scale. As part of the Safeguards team, you'll design and implement ML infrastructure that powers Claude safety. Your work will directly contribute to making AI systems more trustworthy and aligned with human values, ensuring our models operate safely as they become more capable. Responsibilities: Design and build scalable ML infrastructure to support real-time and batch classifier and safety evaluations across our model ecosystem Build monitoring and observability tools to track model performance, data quality, and system health for safety-critical applications Collaborate with research teams to productionize safety research, translating experimental safety techniques into robust, scalable systems Optimize inference latency and throughput for real-time safety evaluations while maintaining high reliability standards Implement automated testing, deployment, and rollback systems for ML models in production safety applications Partner with Safeguards, Security, and Alignment teams to understand requirements and deliver infrastructure that meets safety and production needs Contribute to the development of internal tools and frameworks that accelerate safety research and deployment You may be a good fit if you: Have 5+ years of experience building production ML infrastructure, ideally in safety-critical domains like fraud detection, content moderation, or risk assessment Are proficient in Python and have experience with ML frameworks like PyTorch, TensorFlow, or JAX Have hands-on experience with cloud platforms (AWS, GCP) and container orchestration (Kubernetes) Understand distributed systems principles and have built systems that handle high-throughput, low-latency workloads Have experience with data engineering tools and building robust data pipelines (e.g., Spark, Airflow, streaming systems) Are results-oriented, with a bias towards reliability and impact in safety-critical systems Enjoy collaborating with researchers and translating cutting-edge research into production systems Care deeply about AI safety and the societal impacts of your work Strong candidates may have experience with: Working with large language models and modern transformer architectures Implementing A/B testing frameworks and experimentation infrastructure for ML systems Developing monitoring and alerting systems for ML model performance and data drift Building automated labeling systems and human-in-the-loop workflows Experience in trust & safety, fraud prevention, or content moderation domains Knowledge of privacy-preserving ML techniques and compliance requirements Contributing to open-source ML infrastructure projects Deadline to apply: None. Applications will be reviewed on a rolling basis. The expected salary range for this position is:Annual Salary:$300,000—$405,000 USDLogistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

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We are seeking a Machine Learning Engineer Specialist- AI Trainer to join one of our clients. You'll play a critical role in advancing AI models by reviewing and refining outputs generated by cutting-edge large language models (LLMs). By applying your expertise in machine learning, data science, and technical domains, you'll ensure that model outputs maintain high standards of technical accuracy, relevance, and consistency. This role combines analytical thinking with hands-on data quality work, offering research-grade insights into model evaluation and improvement. Responsibilities:- Use internal tools to evaluate and critique AI-generated outputs, focusing primarily on technical and scientific domains.- Review complex model responses and suggest improvements with an emphasis on clarity, correctness, and domain relevance.- Contribute to the curation and refinement of datasets used to train and fine-tune AI/ML models.- Collaborate closely with cross-functional AI teams to identify data patterns, edge cases, and model blind spots.- Stay updated on model behaviors and guidelines as they evolve, applying sound judgment to nuanced annotation tasks. Qualifications:- MS or PhD in Computer Science, Machine Learning, Data Science, or a related technical field.- Alternatively, 3+ years of professional experience as a Machine Learning Engineer or Data Scientist at a top-tier company (e.g., FAANG, leading startups, AI labs).- Strong grasp of core machine learning concepts, model training workflows, and evaluation strategies.- Experience with LLMs, NLP systems, or applied ML in production settings is highly desirable.- Ability to assess complex technical information and provide constructive, detail-oriented feedback.- Excellent written communication skills, both for technical and explanatory writing.- Ability to operate independently with sound judgment under ambiguous conditions.- Passion for AI development, data quality, and technological advancement. Nice to have:- Publications in machine learning, AI, or computer science journals/conferences.- Experience working with human feedback loops in ML systems (e.g., RLHF, data annotation, model alignment).- Teaching, mentoring, or technical writing experience in ML or related technical domains.- Exposure to generative AI applications or prompt engineering. About RYZ Labs:RYZ Labs is a startup studio built in 2021 by two lifelong entrepreneurs. The founders of RYZ have worked at some of the world's largest tech companies and some of the most iconic consumer brands. They have lived and worked in Argentina for many years and have decades of experience in Latam. What brought them together is the passion for the early phases of company creation and the idea of attracting the brightest talents in order to build industry-defining companies in a post-pandemic world. Our teams are remote and distributed throughout the US and Latam. They use the latest cutting-edge technologies in cloud computing to create applications that are scalable and resilient. We aim to provide diverse product solutions for different industries, planning to build a large number of startups in the upcoming years. At RYZ, you will find yourself working with autonomy and efficiency, owning every step of your development. We provide an environment of opportunities, learning, growth, expansion, and challenging projects. You will deepen your experience while sharing and learning from a team of great professionals and specialists. Our values and what to expect:- Customer First Mentality - every decision we make should be made through the lens of the customer.- Bias for Action - urgency is critical, expect that the timeline to get something done is accelerated.- Ownership -  step up if you see an opportunity to help, even if not your core responsibility. - Humility and Respect - be willing to learn, be vulnerable, and treat everyone who interacts with RYZ with respect.- Frugality - being frugal and cost-conscious helps us do more with less- Deliver Impact - get things done in the most efficient way. - Raise our Standards - always be looking to improve our processes, our team, and our expectations. The status quo is not good enough and never should be.

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We are seeking a Mechanical Engineering Specialist - AI Trainer to join one of our clients. You'll play a crucial role in advancing the capabilities of AI models by evaluating and refining responses in the field of mechanical engineering. Your expertise in areas such as thermodynamics, statics, dynamics, mechanics of materials, and fluid systems will be essential to ensuring the technical accuracy and quality of AI outputs. This role requires domain knowledge, attention to detail, and a passion for improving data quality in AI systems. Responsibilities:- Evaluate and critique AI-generated responses in mechanical engineering, ensuring clarity, correctness, and relevance.- Provide expert feedback on topics like materials science, fluid mechanics, mechanical design, and manufacturing processes.- Help curate and annotate datasets used to fine-tune models with mechanical engineering content.- Identify edge cases, model errors, and technical inaccuracies in engineering outputs.- Collaborate with interdisciplinary AI teams to enhance model understanding and response quality. Qualifications:- PhD or MS in Mechanical Engineering or a closely related field.- Alternatively, 3+ years of professional experience as a Mechanical Engineer in academia, industry, or applied R&D settings.- Solid understanding of mechanical engineering principles, design practices, and simulation tools.- Strong ability to explain complex concepts clearly in writing.- Comfortable with ambiguous tasks and capable of exercising independent judgment in technical assessments.- Excellent attention to detail, especially in technical communication and numerical accuracy. Nice to have:- Experience with CAD tools, FEA, CFD, or robotics systems.- Teaching, tutoring, or curriculum development experience in mechanical engineering.- Publications or technical writing in engineering disciplines.- Exposure to generative AI systems or LLMs.- Experience with RLHF or data annotation for technical domains. About RYZ Labs:RYZ Labs is a startup studio built in 2021 by two lifelong entrepreneurs. The founders of RYZ have worked at some of the world's largest tech companies and some of the most iconic consumer brands. They have lived and worked in Argentina for many years and have decades of experience in Latam. What brought them together is the passion for the early phases of company creation and the idea of attracting the brightest talents in order to build industry-defining companies in a post-pandemic world. Our teams are remote and distributed throughout the US and Latam. They use the latest cutting-edge technologies in cloud computing to create applications that are scalable and resilient. We aim to provide diverse product solutions for different industries, planning to build a large number of startups in the upcoming years. At RYZ, you will find yourself working with autonomy and efficiency, owning every step of your development. We provide an environment of opportunities, learning, growth, expansion, and challenging projects. You will deepen your experience while sharing and learning from a team of great professionals and specialists. Our values and what to expect:- Customer First Mentality - every decision we make should be made through the lens of the customer.- Bias for Action - urgency is critical, expect that the timeline to get something done is accelerated.- Ownership -  step up if you see an opportunity to help, even if not your core responsibility. - Humility and Respect - be willing to learn, be vulnerable, and treat everyone who interacts with RYZ with respect.- Frugality - being frugal and cost-conscious helps us do more with less- Deliver Impact - get things done in the most efficient way. - Raise our Standards - always be looking to improve our processes, our team, and our expectations. The status quo is not good enough and never should be.

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We are seeking a Neuroscience Specialist- AI Trainer. You will play an essential role in supporting the training of AI models focused on cognitive science, brain function, and neural networks by reviewing expert content. Your expertise in neuroscience will ensure the accurate understanding and representation of brain-behavior relationships, disorders, and therapies in AI outputs. Responsibilities:- Evaluate AI-generated neuroscience content across domains such as cognitive psychology, neuroanatomy, and pharmacology.- Provide feedback based on the latest neuroscientific understanding.- Contribute to the development of tools for curating neuro-related content.- Review academic and clinical neuroscience topics for relevance and accuracy.- Apply critical reasoning to identify gaps in AI outputs and suggest improvements. Qualification:- PhD in Neuroscience, Cognitive Science, or a related field.- Familiarity with neuroimaging, neuropsychology, or neural modeling.- Strong writing and research abilities.- Experience in simplifying complex neuroscience concepts for learners.- Passionate about integrating AI in education and research. Nice to have:- Peer-reviewed publications in neuroscience.- Experience teaching or tutoring in neuro fields.- Background in science communication or medical writing.- Exposure to brain-computer interface or neuro-AI research. About RYZ Labs:RYZ Labs is a startup studio built in 2021 by two lifelong entrepreneurs. The founders of RYZ have worked at some of the world's largest tech companies and some of the most iconic consumer brands. They have lived and worked in Argentina for many years and have decades of experience in Latam. What brought them together is the passion for the early phases of company creation and the idea of attracting the brightest talents in order to build industry-defining companies in a post-pandemic world. Our teams are remote and distributed throughout the US and Latam. They use the latest cutting-edge technologies in cloud computing to create applications that are scalable and resilient. We aim to provide diverse product solutions for different industries, planning to build a large number of startups in the upcoming years. At RYZ, you will find yourself working with autonomy and efficiency, owning every step of your development. We provide an environment of opportunities, learning, growth, expansion, and challenging projects. You will deepen your experience while sharing and learning from a team of great professionals and specialists. Our values and what to expect:- Customer First Mentality - every decision we make should be made through the lens of the customer.- Bias for Action - urgency is critical, expect that the timeline to get something done is accelerated.- Ownership -  step up if you see an opportunity to help, even if not your core responsibility. - Humility and Respect - be willing to learn, be vulnerable, and treat everyone who interacts with RYZ with respect.- Frugality - being frugal and cost-conscious helps us do more with less- Deliver Impact - get things done in the most efficient way. - Raise our Standards - always be looking to improve our processes, our team, and our expectations. The status quo is not good enough and never should be.

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About us:At Articul8 AI, we relentlessly pursue excellence and create exceptional AI products that exceed customer expectations. We are a team of dedicated individuals who take pride in our work and strive for greatness in every aspect of our business. We believe in using our advantages to make a positive impact on the world and inspiring others to do the same. Job Description:Articul8 AI is seeking an exceptional Applied AI Researcher to join us in shaping the future of Generative Artificial Intelligence (GenAI). As a member of our Applied Research team, you will be responsible for implementing novel algorithms and models capable of handling diverse modalities such as text, images, audio, video, and time series data.Responsibilities:Serve as the subject matter expert in various domains such as data pipelines, pre-training and post-training, reinforcement learning, model architecture development and optimization, multi-expert systems, and multimodal models and techniques.Play a pivotal role in pioneering technologies through all stages, from initial brainstorming and experimentation to validation and deployment.Collaborate with cross-functional teams to seamlessly incorporate innovation and maintain our product technology leadership.Continuously stay abreast of emerging trends and advancements in of GenAI and associated fields, while disseminating appropriate research results at top-tier conferences and journals.Required Qualifications:Education: PhD degree in Computer Science, Machine Learning (ML), or a related field; or alternatively, MSc Degree and experience (4+ years post BSc graduation) as a practicing researcher.Professional experience: proven track record as a researcher working in the design and implementation of ML/AI models and algorithms aimed at solving complex, real-world problems. A strong background in parallel/distributed computing (preferably on the cloud).Core technical skills: Experience developing tools, libraries, and infrastructure for data preprocessing, model training/finetuning, and deployment of LLMs in research and production environments.Machine learning, deep learning, probability theory and statistics, natural language processing, computer vision, data wrangling and preparation, model evaluation and interpretation.Programming Skills: Proficiency in programming languages such as Python and experience working with version control systems (e.g., Git) and collaborating on code repositories is crucial.Preferred Qualifications:4+ years of hands-on experience as an applied ML/AI researcherExperience with cloud computing platforms such as AWS, Azure, or GCP.Proven track record of publications in top-tier conferences and journalsProfessional Attributes: Problem Solving: ability to break down complex problems into manageable components, devising creative solutions, and iteratively refining ideas based on feedback and experimental evidence. Collaboration and Communication: proficiency in working cross-functionally—communicating clearly, providing constructive criticism, delegating responsibilities, and respecting diverse perspectives. Project Management and Prioritization: demonstrated aptitude in balancing multiple projects, deadlines, and allocating time efficiently between short-term objectives and long-term goals. Critical Thinking: ability to carefully evaluate assumptions, questioning established methodologies, challenging own biases, and maintaining skepticism when interpreting results. Curiosity and Continuous Learning: ability to stay curious about advances in related fields and constantly seeking opportunities to expand knowledge base. Emotional Intelligence and Intellectual Humility: capable of displaying empathy, resilience, adaptability, and self-awareness. Ability to recognize own limitations, embracing uncertainty, acknowledging mistakes, and valuing others' contributions. What We Offer: By joining our team, you become part of a community that embraces diversity, inclusiveness, and lifelong learning. We nurture curiosity and creativity, encouraging exploration beyond conventional wisdom. Through mentorship, knowledge exchange, and constructive feedback, we cultivate an environment that supports both personal and professional development. If you're ready to join a team that's changing the game, apply now to become a part of the Articul8 team. Join us on this adventure and help shape the future of Generative AI in the enterprise.