Top Machine Learning Engineer Jobs Openings in 2025

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<This Is a Remote in the UK> About the Role We are seeking a highly motivated Creative Technologist to join our Applied Research team, reporting to the Head of Applied Research. The successful candidate will focus on advancing generative media research, with a primary emphasis on image models, while also contributing across video, audio, and 3D modalities. In addition to core research, this role will work directly with customers, alongside our Revenue and Sales teams, to design, fine-tune, and deploy custom models, workflows, and creative assets tailored to industries such as E-commerce, VFX, and other visual media. This is a hands-on position at the intersection of cutting-edge research and real-world application. Responsibilities Collaborate with the Applied Research team to develop state-of-the-art generative media solutions, with a strong emphasis on image models. Fine-tune and extend UNet and DiT architectures for generative tasks across multiple modalities (image, video, audio, 3D). Work directly with customers to research, design, and deliver customized models, workflows, and creative assets for applications in E-commerce, VFX, and other visual media sectors. Implement and adapt novel techniques from research papers and repositories into practical, high-quality code. Curate, preprocess, and design high-quality datasets for training and fine-tuning. Collaborate cross-functionally with Product, Engineering, and Commercial teams to ensure smooth integration of models into customer workflows. Stay at the cutting edge of generative modeling research, incorporating advancements into both internal pipelines and customer-facing solutions. Evaluate, benchmark, and optimize models for quality, diversity, and efficiency in generative media applications. Qualifications Proven experience with image models; knowledge of video, audio, or 3D generative models is a strong plus. Strong experience fine-tuning UNet and DiT architectures for generative tasks. Proficiency in Python, with the ability to implement and customize code from research repositories. Solid understanding of machine learning concepts (formal ML background preferred but not required). Experience with Linux, CUDA, and PyTorch in a research or production setting. Demonstrated ability to create customer-specific generative solutions and workflows. Experience managing fine-tuning processes to improve model quality and diversity. Portfolio, GitHub, or prior work showcasing generative media or applied ML research, particularly in E-commerce, VFX, or other visual media contexts, is highly desirable. Equal Employment Opportunity We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability, or other legally protected statuses.

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<This Is a Remote Role> About the Role We are seeking a highly motivated Creative Technologist to join our Applied Research team, reporting to the Head of Applied Research. The successful candidate will focus on advancing generative media research, with a primary emphasis on image models, while also contributing across video, audio, and 3D modalities. In addition to core research, this role will work directly with customers, alongside our Revenue and Sales teams, to design, fine-tune, and deploy custom models, workflows, and creative assets tailored to industries such as E-commerce, VFX, and other visual media. This is a hands-on position at the intersection of cutting-edge research and real-world application. Responsibilities Collaborate with the Applied Research team to develop state-of-the-art generative media solutions, with a strong emphasis on image models. Fine-tune and extend UNet and DiT architectures for generative tasks across multiple modalities (image, video, audio, 3D). Work directly with customers to research, design, and deliver customized models, workflows, and creative assets for applications in E-commerce, VFX, and other visual media sectors. Implement and adapt novel techniques from research papers and repositories into practical, high-quality code. Curate, preprocess, and design high-quality datasets for training and fine-tuning. Collaborate cross-functionally with Product, Engineering, and Commercial teams to ensure smooth integration of models into customer workflows. Stay at the cutting edge of generative modeling research, incorporating advancements into both internal pipelines and customer-facing solutions. Evaluate, benchmark, and optimize models for quality, diversity, and efficiency in generative media applications. Qualifications Proven experience with image models; knowledge of video, audio, or 3D generative models is a strong plus. Strong experience fine-tuning UNet and DiT architectures for generative tasks. Proficiency in Python, with the ability to implement and customize code from research repositories. Solid understanding of machine learning concepts (formal ML background preferred but not required). Experience with Linux, CUDA, and PyTorch in a research or production setting. Demonstrated ability to create customer-specific generative solutions and workflows. Experience managing fine-tuning processes to improve model quality and diversity. Portfolio, GitHub, or prior work showcasing generative media or applied ML research, particularly in E-commerce, VFX, or other visual media contexts, is highly desirable. Equal Employment Opportunity We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability, or other legally protected statuses.

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Magical is redefining how work gets done.Our agentic AI platform brings "AI employees" into the workplace to take over the repetitive, soul-crushing workflows that slow teams down. The result: organizations move faster, with sharper focus, and deliver better outcomes where it matters most, like improving patient care.The shift to agentic work is inevitable, and we’re leading it. We've scaled from $0 -> $XM ARR in 3 months with our agentic product, and we're looking for engineers to help us reach $XXM ARR in the next 9 months. As a founding member of our team you’ll be shaping the playbook for the future of work alongside a small, relentless team pushing the edge of what’s possible with AI.We're backed by the investors behind OpenAI, Anthropic, Huggingface, and Notion, including Greylock, Coatue, and Lightspeed. The runway is long. The ambition is high. And the market is wide open.About the roleDesign and orchestrate agentic workflows by combining AI prompting with Magical’s multi-agent platform, extending its capabilities to solve complex, customer-specific challenges.Act as a technical bridge between customers and Magical’s product and engineering teams, capturing real-world feedback and translating it into platform improvements.Diagnose and resolve issues across deployments, integrations, and performance optimizations, ensuring reliability in high-stakes environments like healthcare.Shape the internal playbook by building tools, documentation, and reference implementations that accelerate future customer rollouts and scale Magical’s multi-agent ecosystem.About youYou have 3+ years of experience in engineering, QA engineering, solutions engineering, or similar technical backgroundYou’re deeply curious about AI prompting, multi-agent systems, and automation. Prior experience here is a plus, but a fast learner with strong fundamentals will thrive.Have a strong bias towards action, a willingness to do whatever it takes, and embody show > tellHave a strong sense of agency, effectively prioritizing and unblocking yourself without much outside input.You thrive in early-stage chaos: you’re excited to define the playbook rather than follow one.Studied science or engineering in college (dropout welcome)Located in SF/Toronto or willing to relocateWhat we offerA chance to be an early team member at a fast-growing, ambitious companyThe opportunity to push the boundaries of what’s possible with AIA modern stack and the latest tools to do your best workCompetitive salary and meaningful equityUnlimited PTOFun team offsites, past trips include Iceland, Lisbon, Cancun, and Costa Rica

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About the teamAdaptive ML is building a reinforcement learning platform to tune, evaluate, and serve specialized language models. We are pioneering the development of task-specific LLMs using synthetic data, creating the foundational tools and products needed for models to self-critique and self-improve based on simple guidelines. Adaptive Engine enables companies to build and deploy the best LLMs for their business. Our founders previously worked together to create state-of-the-art open LLMs. We closed a $20M seed with Index & ICONIQ in early 2024 and are live with our first enterprise customers (e.g., AT&T).At Adaptive ML, our Success team is part of our Technical Staff. Our Technical Staff develops the foundational technology that powers Adaptive ML, while the Success Team ensures our enterprise customers effectively leverage these technologies—particularly through our Adaptive Engine product—to unlock maximum value. About the roleAs an AI Engineer (Pre-Sales) at Adaptive ML, you will be the technical counterpart to our sales team, helping prospective customers understand how Adaptive Engine can solve their hardest problems. You will design and deliver high-impact demos, guide customers through proof of concepts, and develop technical proposals that highlight the differentiated value of our platform and reinforcement learning.Unlike many sales engineering roles, this position is deeply technical. You’ll have the opportunity to use Adaptive Engine hands-on—building demos, fine-tuning LLMs, and standing up pilots that bridge the gap from prospect to customer. You will also help shape the product roadmap by surfacing customer needs and insights.This is an in-person role based in our Toronto or New York offices.Your responsibilitiesPartner with sales to engage with prospects, uncovering business challenges and mapping them to Adaptive ML solutions;Design and deliver compelling technical demos, tailored to specific customer use cases;Lead and manage proof-of-concepts (POCs) and pilots, ensuring technical success and clear business outcomes;Build prototype pipelines and fine-tuned LLMs using Adaptive Engine to showcase production-ready solutions;Translate technical requirements into custom proposals, suggested architectures, and recommendations for customer deployments;Collaborate with our research and product teams to influence roadmap priorities based on customer feedback;Represent Adaptive ML at conferences, webinars, and industry events with technical authority.Your (ideal) backgroundThe background below is only suggestive of a few pointers we believe could be relevant. We welcome applications from candidates with diverse backgrounds; do not hesitate to get in touch if you think you could be a great fit, even if the below doesn't fully describe you.A degree in computer science, or demonstrated experience in software engineering / machine learning;4–8+ years in a pre-sales, solutions engineering, or technical consulting role, ideally in AI/ML or enterprise software;Hands-on experience with data science, machine learning, or NLP; ability to fine-tune or adapt models is a plus;Strong programming skills, with Python required and TypeScript preferred, from quick prototyping to proof-of-concept deployments;Exceptional communication skills—able to clearly explain technical concepts to both technical and non-technical audiences;Curiosity and enthusiasm for generative AI, with a passion for building demos and real-world applications;Empathy, humility, and a collaborative spirit when working with both customers and teammates.BenefitsComprehensive medical (health, dental, and vision) insurance;401(k) plan with 4% matching (or equivalent);Unlimited PTO — we strongly encourage at least 5 weeks each year;Mental health, wellness, and personal development stipends;Visa sponsorship if you wish to relocate to New York or Paris.

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Vatic Labs is a quantitative trading firm in New York and Abu Dhabi.  Our traders, AI researchers, and technologists collaborate to develop autonomous trading agents and cutting edge technology.   As an Quantitative Research Intern at Vatic Labs, you will contribute to the research and development of fully autonomous trading agents with some of the brightest researchers, traders, and technologists in the world. As a part of your internship at Vatic Labs, you will explore vast amounts of market data, research different AI approaches, apply cutting edge machine learning algorithms and statistical approaches to this data to discover and capitalize on trading opportunities. We are seeking researchers who have demonstrated the ability to generate impactful research in their academic pursuits. We foster an open and academic environment, where collaboration is the key to our success. Drawing from our collective backgrounds in Computer Science, Mathematics, Statistics, and Physics, we apply rigorous analytics to test hypotheses derived from years of successful quantitative trading. We are passionate about hiring the best and the brightest, empowering them with the tools and mentorship needed to be successful. If you possess the following, we would love to explore what is available for you with our team: Earned or will earn a PhD or Master's Degree in Computer Science, Statistics, Mathematics, Electrical Engineering, Physics, or related fields Demonstrable experience coding in C++ or Python in a Linux environment Have experience analyzing large datasets with rigorous statistical and machine learning approaches, including classification, clustering, and regression. In depth technical knowledge of AI, deep learning, and machine learning algorithms including strong knowledge of the mathematical underpinnings behind these various methods Have innate curiosity for understanding why and how certain techniques work Have deep knowledge of time-series analysis Advanced knowledge of a high-level language for numerical analysis, Python (numpy/scipy stack) preferred Contribution to AI and ML research communities, top tiered peer reviewed publications, publishing/presenting papers at conferences such as NIPS, ICML,  etc. Have an interest and enthusiasm for learning about financial markets (previous experience not required)

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Welcome to the video first world From your everyday PowerPoint presentations to Hollywood movies, AI will transform the way we create and consume content. Today, people want to watch and listen, not read — both at home and at work. If you’re reading this and nodding, check out our brand video. Despite the clear preference for video, communication and knowledge sharing in the business environment are still dominated by text, largely because high-quality video production remains complex and challenging to scale—until now…. Meet Synthesia We're on a mission to make video easy for everyone. Born in an AI lab, our AI video communications platform simplifies the entire video production process, making it easy for everyone, regardless of skill level, to create, collaborate, and share high-quality videos. Whether it's for delivering essential training to employees and customers or marketing products and services, Synthesia enables large organizations to communicate and share knowledge through video quickly and efficiently. We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. Read stories from happy customers and what 1,200+ people say on G2. In February 2024, G2 named us as the fastest growing company in the world. Today, we're at a $2.1bn valuation and we recently raised our Series D. This brings our total funding to over $330M from top-tier investors, including Accel, Nvidia, Kleiner Perkins, Google and top founders and operators including Stripe, Datadog, Miro, Webflow, and Facebook. What you'll do at Synthesia: The Data team manages the complete lifecycle of data for researchers - from sourcing and large-scale processing to delivering datasets that power our models. Data sits at the heart of our Research efforts and enables all other teams. As part of the Data team, you’ll work with over a million hours of video and audio data.  This role exists at the intersection of applied research, data engineering, and ML infrastructure rather than being a traditional research position. You’ll build the world’s best human-centric data lake by collaborating closely with our model training teams. By understanding their requirements, you’ll extract new features and annotations that elevate our datasets. You should be passionate about enhancing model performance through high-quality, accurate datasets. Our infrastructure and pipelines are in great shape, and this role provides room to not only enhance them but also influence the team’s longer-term strategy. What we're looking for: Background in Computer Science, Computer Vision, or Audio ML Experience working in deep learning teams and production environments Strong Python skills and a passion for clean, maintainable code Hands-on experience with workflow orchestration Interest in large-scale, non-tabular data (video, audio, images) Bonus point if you have experience in:  Processing large volumes of data in the video and/or audio domain Working on the data side of a GenAI product Why join us? We’re living the golden age of AI. The next decade will yield the next iconic companies, and we dare to say we have what it takes to become one. Here’s why, Our culture At Synthesia we’re passionate about building, not talking, planning or politicising. We strive to hire the smartest, kindest and most unrelenting people and let them do their best work without distractions. Our work principles serve as our charter for how we make decisions, give feedback and structure our work to empower everyone to go as fast as possible. You can find out more about these principles here. Serving 50,000+ customers (and 50% of the Fortune 500) We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. Read stories from happy customers and what 1,200+ people say on G2. Proprietary AI technology Since 2017, we’ve been pioneering advancements in Generative AI. Our AI technology is built in-house, by a team of world-class AI researchers and engineers. Learn more about our AI Research Lab and the team behind. AI Safety, Ethics and Security AI safety, ethics, and security are fundamental to our mission. While the full scope of Artificial Intelligence's impact on our society is still unfolding, our position is clear: People first. Always.  Learn more about our commitments to AI Ethics, Safety & Security. The good stuff... Competitive compensation (salary + stock options + bonus) Hybrid work setting with an office in London, Amsterdam, Zurich, Munich, or remote in Europe.  25 days of annual leave + public holidays Great company culture with the option to join regular planning and socials at our hubs + other benefits depending on your location   #LI-MD1  

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Perplexity is an AI-powered answer engine founded in December 2022 and growing rapidly as one of the world’s leading AI platforms. Perplexity has raised over $1B in venture investment from some of the world’s most visionary and successful leaders, including Elad Gil, Daniel Gross, Jeff Bezos, Accel, IVP, NEA, NVIDIA, Samsung, and many more. Our objective is to build accurate, trustworthy AI that powers decision-making for people and assistive AI wherever decisions are being made. Throughout human history, change and innovation have always been driven by curious people. Today, curious people use Perplexity to answer more than 780 million queries every month–a number that’s growing rapidly for one simple reason: everyone can be curious. Perplexity is looking for an Applied ML Engineer to design, build, and iterate on cutting-edge AI models powering our core experience. As an expert in machine learning and artificial intelligence, you will develop scalable and impactful solutions for user personalization, query understanding, and content discovery - fulfilling the curiosity of millions of users across the globe. Key Responsibilities Apply state-of-the-art ML and LLM techniques to solve problems spanning: Personalization (LLM memory, context summarization, retrieval and ranking); Query Understanding (intent modeling, rewriting, agentic decomposition); Content Discovery (feed ranking and surfacing) Rigorously evaluate LLM/ML models with both offline and online techniques, designing experiments and metrics that provide deep insight into quality and impact. Own the entire model lifecycle from research to production: data analysis, modeling, evaluation, offline/online A/B testing, and iterative improvement. Collaborate cross-functionally with engineers, PMs, data scientists, and designers to ensure our AI drives meaningful product improvements. Stay at the forefront of ML/AI innovation by evaluating and incorporating emerging research and algorithms into the product lifecycle. Preferred Qualifications 5+ years experience building and shipping robust ML/AI models for large-scale, user-facing or data-driven products. Deep expertise in deep learning (PyTorch, TensorFlow, JAX), LLMs, information retrieval, content summarization, recommendation systems, NLP, and/or ranking. Strong software engineering skills (Python, production-quality codebases, collaborative development). In-depth experience with the full ML lifecycle: data analysis, feature engineering, iterative model development, rigorous evaluation, and ongoing monitoring/improvement. Proven collaborator and communicator; excels in high-velocity, cross-functional teams. Curious, driven by end-user/product impact, and passionate about advancing the state of applied ML and AI. BS, MS, or PhD in Computer Science, Engineering, or related field (or equivalent experience). Bonus Points For Experience with LLM prompt engineering, Retrieval-augmented generation (RAG) based systems. Experience in large scale user-centric and content-centric personalization challenges (user modeling, retrieval, content ranking, etc). Open-source or published contributions in ML, NLP, IR, or relevant research fields.  

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About us PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.  Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals. Who We're Looking For As a Senior Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used. You’ve shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools and make pragmatic product decisions that set Delivery up for success. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products. With at least 3 years industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready to not only execute but also lead and mentor others. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.   This Role  As a Senior MLE, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes. You'll: Own the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time‑series forecasting, anomaly detection, optimization & control) to customer production environments. Communicate results and trade‑offs to senior stakeholders; steer roadmaps and influence product direction with evidence. Lead scoping and architecture design for data/ML systems; define success metrics, delivery plans and quality bars. Excel at building robust and scalable ML systems, training and inference pipelines and APIs, running both on cloud and on-prem environments. The tech stack you will use for this includes: Python, PyTorch, Pandas, fastAPI, Scipy, Kubeflow, among others. Mentor and develop engineers and data scientists; provide technical direction and clear, calm decision‑making under pressure. Travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site. Own the scoping of new projects and work-streams with existing customers and taking part in bringing new customers to PhysicsX. As a senior member of the team, you’ll significantly influence our technical direction and will be involved in shaping future solutions and products, while developing your skills as a technical leader. Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you’ll contribute to this exciting journey!      What we offer Equity options – share in our success and growth. 5% 401(k) match – invest in your future. Flexible working – balance your work and life in a way that works for you. Hybrid setup – enjoy our Manhattan office while keeping remote flexibility. Enhanced parental leave – support for life’s biggest milestones. Private healthcare – comprehensive coverage for you and your family. Personal development – access learning and training to help you grow. Work from anywhere – extend your remote setup to enjoy the sun or reconnect with loved ones.   Salary range: $120,000 - 240,000 depending on experience  Seniority will be assessed throughout our interview process   We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.    We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.   

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Location: San Francisco, Bay Area Team: Customer Success | Reports to Head of Customer OperationsAbout TomaAt Toma, we’re building something unorthodox — a fully AI-driven voice platform reshaping how 18,000 car dealerships operate. Our proprietary voice AI handles inbound calls, sets appointments, and unlocks agentic workflows that reduce frontline workload.We’re a 20-person team (ex-Scale AI, Uber, pro Valorant player, robotics champ, motocross racer...) obsessed with getting dealers real results. We’ve landed dozens of rooftops via word-of-mouth, and we’re just getting started.The RoleWe’re looking for a Prompt Engineer & Support Specialist to help us scale fast — without breaking.You’ll be the first technical hire on the support side, working directly with our customers, Ops, Engineering, and Product to solve issues. When you're not solving issues, you'll be laying the foundation for a scalable support motion and building internal health monitoring systems. While this role is a ticket-based support function which includes heavy prompt engineering... We aim for this person to grow into a part forward deploy, part triage lead, part system builder. You’ll get deep in the weeds, own high-impact technical problems, and play a foundational role in how support functions at Toma as we scale.What You’ll Do Right Now Technical Debugging & TriageManage a support queue & build systems to improve support metrics. Extensive prompt engineering to solve real world business problemsInvestigate LLM-related issues, agent behavior, voice system bugs, and integration failuresReproduce edge cases and partner with Engineering to drive root-cause fixesTriage and document inbound issues for the product and AI teamsWhat You'll Grow Into Build Support ProcessesBe the connective tissue between Engineering, Ops, and ProductOwn and improve the way support is delivered and scaled: ticket systems, SOPs, playbooksBuild an internal knowledge base for common issues and config workflows Build Health Monitoring & ToolingDesign and implement health monitoring for AI behavior, call routing, scheduler integrations, and moreCreate dashboards, logs, and alerting systems to reduce support lagWrite light internal scripts and tools to automate repetitive ops or support tasksYou Might Be a Fit If You...Have 2–5 years in a technical support, infra, dev ops, or forward deploy role, ideally at a startup with extensive customer facing experience. Love solving messy technical problems in live customer environmentsCan read logs, reproduce bugs, and work directly with engineers on triageHave experience with AI systems (LLMs, agents, vector databases) or are excited to learn fastCan write basic scripts (Python, JS, Bash, SQL, etc.) to unblock yourself or automate tasksThrive in ambiguity and want to build support systems from scratch — not inherit themNice to HaveExperience with tools like Eleven Labs, Metabase, DataDog, or voice AI platformsBackground in automotive, SaaS, or customer-facing AI productsStartup experience where you’ve been “the one who gets called when it breaks”Why This Role MattersWe’re growing fast, and every new customer means more complexity. The systems you build — and the fires you put out — will directly shape our ability to scale, retain, and grow revenue across hundreds of rooftops. You won’t just answer tickets. You’ll own the support systems that reduce customer effort & pain.What Success Looks LikeYou become the go-to point of contact for incoming support tickets You reduce our average support resolution time through better tools, monitoring, and triageYou help launch a proactive support function — not just reactive firefightingYou elevate how Toma learns from customer pain, product bugs, and systemic issuesCompensation & PerksCompetitive salary and early-stage equityHealth, dental, visionDaily food stipend Health & wellness stipend Educational stipendHigh-impact seat on a low-ego, high-output team

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About LightfieldLightfield is a next-generation CRM that automatically captures customer interactions like emails, meetings, and support tickets and organizes them into structured CRM data, enabling deep analysis of customer activity and powerful automation.Unlike traditional CRMs, Lightfield continuously learns from how you sell and who you sell to, directly from the words of customers and actual workflows in the system. With this data, Lightfield proactively manages customer tasks, automates personalized customer communication, and delivers the visibility and insights needed for teams to continually refine their go-to-market strategy.The company is initially focused on becoming the first comprehensive system of record and go-to-market platform for high-growth technology companies. With a flexible and scalable model for data capture and organization, Lightfield is designed to be the last CRM and GTM-automation tool our companies will ever need.Our team previously built Tome, a generative AI presentation product used by over 25 million people, gaining deep expertise in context management, effective evaluation loops, and user-interaction design for generative AI. Before Tome, many of us worked on Llama, Instagram, Facebook Messenger, Pinterest, and Salesforce.About the roleWe’re looking for a driven, creative engineer who is excited about the challenge of leveraging LLMs to build exceptionally innovative product experiences.You’ll join us at the frontier of AI product development, developing industry-leading approaches to solve important customer problems.Engineers at Lightfield own and drive projects from inception to impact, working with teammates of all functions along the way.You’ll also push our company’s overall product and technical vision as we learn from each project and continue to scale.What You'll doCollaborate with product leaders to identify customer problems, scope requirements, and implement LLM-powered solutions.Apply LLMs as reasoning engines to build domain-specific AI assistants.Create and enhance prompts, applying techniques like few-shot learning and chain-of-thought.Develop and optimize end-to-end RAG pipelines and agent architectures to leverage public and proprietary data.Improve end-to-end AI agent quality (e.g. relevance, fidelity, latency) via empirical evaluation and iteration.Build and enhance systems and tools that enable high-velocity experimentation (e.g. LLM-powered automated evaluation) and customized product experiences.Stay at the forefront of AI research and incorporate state-of-the-art techniques.Shape technical direction and best practices for AI application development at Lightfield.Help build a world-class engineering team by recruiting and mentoring teammates.Who you areYou have the ability to ramp quickly on tech stack that features TypeScript, React, Next.js, Node.js, Apollo GraphQL, and Aurora PostgreSQL.You have explored working with LLMs, either through professional projects or personal experimentation.You have a degree in Computer Science or a related field, with a strong foundation in software engineering principles.You are familiar with AI and ML concepts (e.g. training, evaluation techniques).You are passionate about keeping up with and exploring the latest advancements in LLMs and LLMOps (including open source solutions, e.g. LangChain).You are excited to develop new best practices in an emerging domain.You can drive a project with an ambiguous problem independently.You enjoy strategically balancing ambitious vision with frequent delivery of user value.You are able to clearly communicate your reasoning and decisions to your teammates (technical and nontechnical) at an appropriate altitude of detail.You are energized by building software experiences customers will use directly and depend on to do their jobs successfully.Benefits & PerksCompetitive salaryMeaningful early equityHealth insurance (medical, dental, vision)3 weeks of PTO11 paid company holidays + we enjoy a winter holiday break3 months of paid family leaveWednesdays work from homeRegular team dinners, events, offsites, and retreats401k planOther perks include: commuter and lunch stipend

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About Us Observe.AI enables enterprises to transform how they connect with customers - through AI agents and copilots that engage, assist, and act across every channel. From automating conversations to guiding human agents in real time to uncovering insights that shape strategy, Observe.AI turns every interaction into a driver of loyalty and growth. Trusted by global leaders, we’re creating a future where every customer experience is smarter, faster, and more impactful. Why Join Us At our core, we are shaping how AI transforms real-world challenges in the contact center space. As part of our world-class ML team, you’ll work on developing cutting-edge LLM-powered solutions & Agentic AI, building end-to-end processing pipelines, and handling production challenges at scale—millions of interactions daily—while shaping the future of AI-powered contact centers.  If you are truly an engineer at heart, excited about turning breakthroughs in multi-agent systems, LLMs, NLP, and ML into practical outcomes through applied research, and building scalable production systems to create real product impact, you will feel right at home at Observe.AI. You’ll also have the opportunity to publish in top conferences, and influence Observe.AI’s product and platform strategy.  Beyond the tech, you’ll join a collaborative, mission-driven culture where innovation, impact, and fun go hand in hand. We value curiosity, collaboration, and the courage to push boundaries. What you’ll be doing Design & develop state-of-the-art LLM-powered AI capabilities and Agentic AI/ Multi-agent systems end-to-end, from ideation to production for Observe.AI’s product offerings, in a fast-paced startup environment. Work with cutting-edge tools and technologies in Machine Learning, Deep Learning & Natural Language Processing, including LLMs and LLM-powered technologies/ paradigms, including Agentic AI. Build/ maintain highly scalable production systems that power AI capabilities on Observe.AI product/ platform. Optimize ML models and processing pipelines for performance, cost-effectiveness, and scale. Work with a world-class ML team in building exciting stuff, mentor juniors, and influence peers/ stakeholders. Collaborate cross-team with engineers, product managers, customer-facing teams, and customers to understand pain points and business opportunities to build the right solution for the right problem. Keep up-to-date with the latest ML/ DL/ NLP literature and influence the technological evolution of Observe.AI platform. Contribute to the community through tech blogs and publishing papers in ML/ NLP conferences like EMNLP, ACL, etc. What you’ll bring to the role Bachelor’s or Master’s degree in Computer Science or related disciplines from a top-tier institution with exposure to ML/ DL/ NLP/ NLU. An engineering mindset with the competencies of an applied scientist.  3+ years of industry experience in building large-scale NLP/ NLU systems, with recent experience in building LLM-powered applications and Agentic systems. Strong understanding of the fundamentals of ML and NLP/ NLU, and practical aspects of building ML systems in production; backed by extensive hands-on experience in building/ scaling customer-facing ML/ NLP/ NLU applications. Good understanding of recent advances in building LLM-powered applications,  and multi-agent systems at scale.  Excellent implementation skills in Python and Machine Learning Frameworks such as Pytorch, Tensorflow, HuggingFace, etc., and deploying/ maintaining scalable machine learning systems in production. Ability to provide thought leadership in one or more technical areas of interest to Observe.AI, and influence product development Excellent communication, collaboration skills, and presentation skills. Experience with Spoken Language Understanding is a plus Published papers in top NLP/ NLU conferences or workshops are a plus Relevant open-source contributions are a plus. Perks & Benefits Excellent medical insurance options and free online doctor consultations Yearly privilege and sick leaves as per Karnataka S&E Act Generous holidays (National and Festive) recognition and parental leave policies Learning & Development fund to support your continuous learning journey and professional development Fun events to build culture across the organization Flexible benefit plans for tax exemptions (i.e. Meal card, PF, etc.) Our Commitment to Inclusion and Belonging Observe.AI is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Observe AI does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Observe.AI also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. We welcome all people. We celebrate diversity of all kinds and are committed to creating an inclusive culture built on a foundation of respect for all individuals. We seek to hire, develop, and retain talented people from all backgrounds. Individuals from non-traditional backgrounds, historically marginalized or underrepresented groups are strongly encouraged to apply. If you are ambitious, make an impact wherever you go, and you're ready to shape the future of Observe.AI, we encourage you to apply. For more information, visit www.observe.ai.

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Building the Future of Open Source + Decentralized AIPrime Intellect is building the open superintelligence stack - from frontier agentic models to the infra that enables anyone to create, train, and deploy them. We aggregate and orchestrate global compute into a single control plane and pair it with the full rl post-training stack: environments, secure sandboxes, verifiable evals, and our async RL trainer. We enable researchers, startups and enterprises to run end-to-end reinforcement learning at frontier scale, adapting models to real tools, workflows, and deployment contexts.We recently raised $15mm in funding (total of $20mm raised) led by Founders Fund, with participation from Menlo Ventures and prominent angels including Andrej Karpathy (Eureka AI, Tesla, OpenAI), Tri Dao (Chief Scientific Officer of Together AI), Dylan Patel (SemiAnalysis), Clem Delangue (Huggingface), Emad Mostaque (Stability AI) and many others.Role ImpactThis is a hybrid position spanning cloud LLM serving, LLM inference optimization and RL systems. You will be working on advancing our ability to evaluate and serve models trained with our Environment Hub at scale. The two key areas are:Building the infrastructure to serve LLMs efficiently at scale.Optimization and integration of inference systems into our RL training stack.Core Technical ResponsibilitiesLLM ServingMulti‑tenant LLM Serving: Build a multi-tenant LLM serving platform that operates across our cloud GPU fleets.GPU‑Aware Scheduling: Design placement and scheduling algorithms for heterogeneous accelerators.Resilience & Failover: Implement multi‑region/zone failover and traffic shifting for resilience and cost control.Autoscaling & Routing: Build autoscaling, routing, and load balancing to meet throughput/latency SLOs.Model Distribution: Optimize model distribution and cold-start times across clusters.Inference Optimization & PerformanceFramework Development: Integrate and contribute to LLM inference frameworks such as vLLM, SGLang, TensorRT‑LLM.Parallelism and Configuration Tuning: Optimize configurations for tensor/pipeline/expert parallelism, prefix caching, memory management and other axes for maximum performance.End‑to‑End Performance: Profile kernels, memory bandwidth and transport; apply techniques such as quantization and speculative decoding.Perf Suites: Develop reproducible performance suites (latency, throughput, context length, batch size, precision).RL Integration: Embed and optimize distributed inference within our RL stack.Platform & ToolingCI/CD: Establish CI/CD with artifact promotion, performance gates, and reproducible builds.Observability: Build metrics, logs, tracing; structured incident response and SLO management.Docs & Collaboration: Document architectures, playbooks, and API contracts; mentor and collaborate cross‑functionally.Technical RequirementsRequired ExperienceBuilding ML Systems at Scale: 3+ years building and running large‑scale ML/LLM services with clear latency/availability SLOs.Inference Backends: Hands‑on with at least one of vLLM, SGLang, TensorRT‑LLM.Distributed Serving Infra: Familiarity with distributed and disaggregated serving infrastructure such as NVIDIA Dynamo.Inference Internals: Deep understanding of prefill vs. decode, KV‑cache behavior, batching, sampling, speculative decoding, parallelism strategies.Full‑Stack Debugging: Comfortable debugging CUDA/NCCL, drivers/kernels, containers, service mesh/networking, and storage, owning incidents end‑to‑end.Infrastructure SkillsPython: Systems tooling and backend services.PyTorch: LLM Inference engine development and integration, deployment readiness.Cloud & Automation: AWS/GCP service experience, cloud deployment patterns.Kubernetes: Running infrastructure at scale with containers on Kubernetes.GPU & Networking: Architecture, CUDA runtime, NCCL, InfiniBand; GPU‑aware bin‑packing and scheduling across heterogeneous fleets.Nice to HaveKernel‑Level Optimization: Familiarity with CUDA/Triton kernel development; Nsight Systems/Compute profiling.Systems Performance Languages: Rust, C++.Data & Observability: Kafka/PubSub, Redis, gRPC/Protobuf; Prometheus/Grafana, OpenTelemetry; reliability patterns.Infra & Config Automation: Terraform/Ansible, infrastructure-as-code, reproducible environmentsOpen Source: Contributions to serving, inference, or RL infrastructure projects.What We OfferCompetitive compensation with significant equity incentivesFlexible work arrangement (remote or San Francisco office)Full visa sponsorship and relocation supportProfessional development budgetRegular team off-sites and conference attendanceOpportunity to shape decentralized AI and RL at Prime IntellectGrowth OpportunityYou'll join a team of experienced engineers and researchers working on cutting-edge problems in AI infrastructure. We believe in open development and encourage team members to contribute to the broader AI community through research and open-source contributions.We value potential over perfection. If you're passionate about democratizing AI development, we want to talk to you.Ready to help shape the future of AI? Apply now and join us in our mission to make powerful AI models accessible to everyone.

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About Faculty At Faculty, we transform organisational performance through safe, impactful and human-centric AI. With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme. Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI. Should you join us, you’ll have the chance to work with, and learn from, some of the brilliant minds who are bringing Frontier AI to the frontlines of the world.About the RoleAs a Machine Learning Engineer in our Professional and Financial Services business unit, you will work on project teams delivering bespoke machine learning solutions to our clients. You will be responsible for implementing data-driven approaches, contributing to the design of scalable software architectures, and ensuring best practices are followed throughout development.You will collaborate closely with our commercial team to help shape and deliver high-quality projects. In the early stages of client engagements, you will contribute to defining the technical scope, ensuring that proposed solutions are both feasible and aligned with business objectives. Your work will play a critical role in ensuring we deliver impactful software within agreed timeframes.This role offers the opportunity to apply cutting-edge machine learning techniques to complex challenges in professional and financial services, while working alongside colleagues from diverse technical and commercial backgrounds. What You'll Be DoingYou are engineering-focused, with a keen interest and working knowledge of operationalised machine learning. You have a desire to take cutting-edge ML applications into the real world. You will develop new methodologies and champion best practices for managing AI systems deployed at scale, with regard to technical, ethical and practical requirements. You will support both technical, and non-technical stakeholders, to deploy ML to solve real-world problems. Our Machine Learning Engineers are responsible for the engineering aspects of our customer delivery projects. As a Machine Learning Engineer, you’ll be essential to helping us achieve that goal by:Building software and infrastructure that leverages Machine Learning;Creating reusable, scalable tools to enable better delivery of ML systemsWorking with our customers to help understand their needsWorking with data scientists and engineers to develop best practices and new technologies; andImplementing and developing Faculty’s view on what it means to operationalise ML software.As a rapidly growing organisation, roles are dynamic and subject to change. Your role will evolve alongside business needs, but you can expect your key responsibilities to include:Working in cross-functional teams of engineers, data scientists, designers and managers to deliver technically sophisticated, high-impact systems.Working with senior engineers to scope projects and design systemsProviding technical expertise to our customersTechnical DeliveryWho We're Looking ForYou can view our company principles here. We look for individuals who share these principles and our excitement to help our customers reap the rewards of AI responsibly.To succeed in this role, you’ll need the following - these are illustrative requirements and we don’t expect all applicants to have experience in everything (70% is a rough guide):Understanding of, and experience with the full machine learning lifecycleWorking with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorchExperience with software engineering best practices and developing applications in Python.Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one of the 3 major cloud providers (AWS, GCP or Azure)Demonstrable experience with containers and specifically Docker and KubernetesAn understanding of the core concepts of probability and statistics and familiarity with common supervised and unsupervised learning techniquesDemonstrable experience of managing/mentoring more junior members of the team Outstanding verbal and written communication.Excitement about working in a dynamic role with the autonomy and freedom you need to take ownership of problems and see them through to executionWe like people who combine expertise and ambition with optimism -- who are interested in changing the world for the better -- and have the drive and intelligence to make it happen. If you’re the right candidate for us, you probably:Think scientifically, even if you’re not a scientist - you test assumptions, seek evidence and are always looking for opportunities to improve the way we do things.Love finding new ways to solve old problems - when it comes to your work and professional development, you don’t believe in ‘good enough’. You always seek new ways to solve old challenges.Are pragmatic and outcome-focused - you know how to balance the big picture with the little details and know a great idea is useless if it can’t be executed in the real world.What we can offer you: The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. Faculty is the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you’ll learn something new from everyone you meet.

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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 and fix and verify exploitable attack vectors before criminals exploit them. Our flagship product, the NodeZeroTM 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. Overview Join Horizon3 to help pioneer AI Offensive Security (AI OffSec)—where machine learning and cybersecurity collide. We’re seeking junior engineers with a strong AI/ML foundation—especially those eager to explore reinforcement learning (RL) and modern model-tuning methods—to build intelligent agents that probe networks, discover vulnerabilities, and emulate real adversaries. You’ll help design, train, and test AI systems that continuously learn to think and act like attackers.Essential FunctionsDevelop AI systems for vulnerability detection and autonomous security testingDesign and train reinforcement-learning and fine-tuning workflows (e.g., PPO, LoRA/QLoRA) to improve automated security agentsAutomate security testing pipelines with Python and modern ML frameworksContribute to feature development from concept through deployment, including model evaluation and experiment trackingIdentify and document vulnerabilities in AI-native applications and LLM workflowsResearch emerging AI security threats, prompt-injection tactics, and adversarial MLDocument findings and help build a technical knowledge base Core Competencies / RequirementsBachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Software Engineering, Mathematics, Statistics, or a related fieldStrong Python skills and comfort with data-science libraries (NumPy, pandas, scikit-learn)Foundational knowledge of AI/ML concepts and frameworks (PyTorch, TensorFlow, or JAX)Exposure to reinforcement learning or similar methods (deep Q-learning, PPO) through coursework, labs, or projectsUnderstanding of model training life cycle: data prep, feature engineering, and evaluationExperience with Linux environments and Git version controlInterest in cybersecurity and ethical hackingStrong problem-solving and clear communication skillsMust be located in or willing to relocate to the Indianapolis metropolitan area Desired / Nice to HaveHands-on projects fine-tuning LLMs or training LoRA/QLoRA adaptersExperience with vector databases or retrieval-augmented generation (RAG)Familiarity with AI security topics (model inversion, adversarial attacks)Internship or academic work in reinforcement learning or autonomous agentsContributions to open-source RL or adversarial-ML projectsExperience with Docker and containerized ML ops (Docker/Kubernetes)Experience with cloud platforms (AWS, Azure, or GCP)Security certifications (Security+, etc.) or active pursuit of themParticipation in CTF platforms (Hack The Box, TryHackMe, etc.) or AI/ML competitions (Kaggle) What We OfferDeep Mentorship: Work side-by-side with experienced engineers to master real-world AI security pipelinesCareer Growth: Opportunity to become a core technical leader as our AI offensive security stack expandsHybrid Flexibility: 2–3 days a week in our Indianapolis office with flexible remote optionsCompetitive Entry-Level Compensation: Full benefits including health, vision, and dental Ideal MindsetEager to learn and grow in both AI and cybersecuritySelf-motivated, detail-oriented, and collaborative Curious “hacker mindset” with a drive to experiment and break things safely Perks 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, equity and benefits. Our benefits include health, vision & dental insurance for you and your family, a flexible vacation policy, and generous parental leave.Compensation and ValuesAt Horizon3, we believe that our people are our greatest asset, and our compensation philosophy reflects this core value. We are committed to fostering an environment where all employees feel valued, respected, and rewarded for their contributions. Our compensation structure is designed to be fair, competitive, and transparent, ensuring that every team member is recognized and compensated equitably across roles, levels, and locations.Additional compensation: All full-time roles are eligible for an equity package in the form of stock options.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 UsConsole is an AI platform that automates IT and internal support. We help companies scale without scaling headcount, and give employees instant resolution to their issues. Our agents understand the full context of the organization, handle requests end-to-end and pull in humans only when necessary.Today, companies like Ramp, Scale, Webflow, and Flock Safety rely on Console to automate over half of their IT & HR requests. We've won every bake-off against our competitors, closed every trial customer and expect to 10x usage by year-end.We're a small, talent-dense team: naturally curious, high-agency and low-ego. Our organization is very flat and ideas win on merit, not hierarchy. We're hiring exceptional people to keep up with demand. We're backed by Thrive Capital and world-class angels.About the roleAs the Head of Applied AI at Console, you'll be responsible for directing AI efforts across the company and product. You will work directly with the founders and product leadership to define the applied AI and research roadmap, and push the frontier of AI agent capabilities in our vertical.You will architect and guide AI development across the company, and create the infrastructure necessary to support a growing team of AI engineers to experiment and contribute effectively. You will analyze frontier research and help inform the strategic technical bets the company will make as we scale up, and be measured on the results.This role is based in San Francisco, CA. We work in-person and offer relocation assistance to new employees.About youYou're an engineering leader with exceptionally strong generalist technical skills, and you have a proven track record of delivering great AI experiences for users and customersYou have great taste; you understand that the best AI experiences feel great to use and you know how to cultivate a culture that obsesses over getting the details rightYou've designed and deployed AI systems in production, hands-on. You know how to iterate on these systems in a way that measurably moves the product forwardYou have a strong grasp on frontier research and understand how to translate that understanding into resultsYou're not dogmatic; you can synthesize your past learnings with new discoveries that challenge them. You have a track record of developing mastery over new domainsRequirements6+ years of full-time software engineering experience, with a track record of AI product engineering or applied ML experienceProven ability to keep up with and synthesize frontier research in a practicable wayComfortable working and contributing across our entire stack (Typescript/Node/React)Obsessed with building incredible product experiences for users, and never happy with "good enough"Why join Console?Product-market fit: We have built the leading product in our category, in a massive market. We've hit an inflection point and are on track to build a generational company. World-class team: We seek high agency contributors who are comfortable navigating ambiguity, ruthlessly prioritize what matters and are action-biased.Grow with us: We reward impact, not credentials or years of experience. We intend to grow talent from within as we scale up.Competitive pay and benefits: top compensation with full benefits including:Equity with early exercise & QSBS eligibilityComprehensive health, dental, and vision insuranceUnlimited PTO401(k)Meals provided daily in office

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you.com is an AI-powered search and productivity platform designed to empower users with personalized, efficient, and trustworthy search experiences. As a cutting-edge technology company, we combine advanced AI models with user-first principles to deliver tools that enhance discovery, creativity, and productivity. At you.com, we are on a mission to create the most helpful search engine in the world—one that prioritizes transparency, privacy, and user control. We’re building a team of innovators, problem-solvers, and visionaries who are passionate about shaping the future of AI and technology. At you.com, you’ll have the opportunity to work on impactful projects, collaborate with some of the brightest minds in the industry, and grow your career in an environment that values creativity, diversity, and curiosity. If you’re ready to make a difference and help us revolutionize the way people search and work, we’d love to have you join us!  About the Role AI is transforming how enterprises sell, support, and operate — surfacing hidden knowledge, automating workflows, and collapsing weeks of effort into minutes. As a Senior AI Engineer, Enterprise Solutions, you’ll act like a startup CTO, turning this vision into robust, production-ready AI solutions that ship fast and deliver measurable wins for our customers. You will get a front seat to AI applications in the economy along with defining and shaping the future.   Responsibilities  Build and Ship: Design and develop AI applications primarily in Python. Run evaluations to validate models and package solutions for Kubernetes, AWS, or adapt them to customer on-premises clusters. Work with Customers: Lead discovery sessions, guide pilot projects, and ensure successful deployments. Collaborate mostly remotely with occasional on-site workshops. Run and Improve: Monitor system performance and reliability. Add to the logging, billing and auth services. Build internal tooling to automate repetitive tasks. Share What You Learn: Provide feedback on patterns, pain points, and reusable modules to the core product team to influence the future direction of the AI platform.   Qualifications Required: 5+ years of experience writing solid production-quality software. Hands-on experience with LLMs and a solid understanding of machine learning fundamentals. Strong customer empathy: ability to listen, ask insightful questions, and translate real-world pain points into intuitive technical designs. Product-minded approach: focus on outcomes, comfortable shaping scope with product managers, defining success metrics, and making trade-offs to accelerate learning. Excellent communication skills, able to engage effectively with executives and engineers both remotely and on-site. Versatile problem-solver who thrives in ambiguous environments and enjoys rapid learning. Nice to Have: Experience in forward-deployed or product-oriented roles. Exposure to regulated industries such as healthcare or finance. Proficiency with Terraform or Pulumi and experience across multiple cloud platforms. Experience integrating with ERP, CRM, or other large enterprise systems. Experience mentoring junior engineers or leading small technical teams. Our salary bands are structured based on a combination of geographic tiers and internal leveling. Compensation is determined by multiple factors assessed during the interview process, with the final offer reflecting these considerations.Salary Band$200,000—$270,000 USDCompany Perks: Hubs in San Francisco and New York City offering regular in-person gatherings and co-working sessions Flexible PTO with U.S. holidays observed and a week shutdown in December to rest and recharge* A competitive health insurance plan covers 100% of the policyholder and 75% for dependents* 12 weeks of paid parental leave in the US* 401k program, 3% match - vested immediately!* $500 work-from-home stipend to be used up to a year of your start date* $1,200 per year Health & Wellness Allowance to support your personal goals* The chance to collaborate with a team at the forefront of AI research *Certain perks and benefits are limited to full-time employees only   you.com is an E-Verify employer. We are also an inclusive, equitable, and accessible workplace. Please let us know if you require accommodation for any portion of the recruitment and hiring process.

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Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.As a Lead Machine Learning Engineer on the AI Models team at Tenstorrent, you’ll guide the development and optimization of cutting-edge AI models for our custom AI devices. You’ll take the lead on shaping technical direction and ensuring the team delivers impactful results. If you enjoy blending hands-on ML engineering with mentoring and strategic decision-making, you’ll thrive here. This role is remote, based in Cyprus. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.   Who You Are Confident with Python programming and hands-on experience with PyTorch for developing deep learning models. Possess a deep understanding of ML model architectures, with the ability to optimize both individual components and overall model performance. Skilled at mentoring engineers, providing technical guidance, and fostering a collaborative team culture. Comfortable leading cross-functional discussions, setting priorities, and aligning efforts toward impactful results.   What We Need Lead the bring-up of state-of-the-art ML models on new hardware platforms. Direct debugging and performance tuning efforts to improve accuracy, efficiency, and robustness. Oversee model optimization techniques, like quantization, flash attention, kernel fusing, and multi-device parallelization. Champion a curiosity-driven approach by staying ahead of ML research trends and guiding the team in applying relevant advances to solve real-world engineering challenges.   What You Will Learn How to lead the deployment of real ML models at scale on a custom AI accelerator. Methods to coordinate model optimization from application to silicon level. Approaches for bridging research innovations with production-ready engineering. How to influence compiler, kernel, and hardware roadmaps through model performance insights.   Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology.  Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2).   These requirements apply to persons located in the U.S. and all countries outside the U.S.  As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency.  If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

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About LangChain: At LangChain, our mission is to make intelligent agents ubiquitous. We help developers build mission-critical AI applications across the entire agent development lifecycle. Our open source frameworks — LangChain and LangGraph — see over 70+ million downloads per month. Developers rely on LangChain for composable integrations and LangGraph for controllable agent orchestration. Our commercial agent platform, consisting of LangSmith and LangGraph Platform, enables teams to build, test, run, and manage agents at scale across their organization.Founded in 2023, LangChain powers top engineering teams at companies like Replit, Lovable, Clay, Klarna, LinkedIn, and more.About the role:Our Applied AI team is the core team actually building AI products. In this role you’ll implement various AI powered workflows, agents and full-stack applications. The workflows and applications you build will be for both internal usage and customer facing products. Much of the work you do will be open-sourced helping advance the OSS AI ecosystem. This role is onsite in San Francisco (preferred), New York, or Boston.You will:Implement AI workflows/applications end to end.Stay up to date with progress in agent development, and implementation techniques.Design and iterate on novel AI architectures to solve real world tasks.Build evaluation pipelines to test the agents you implement.How to be successful in this role:3+ years of software engineering experience including 1+ year building AI applications professionally.Experience implementing evaluations for agents/workflows.A subject matter expert in the components that make up an AI application, and how/when to best utilize each: prompting/context engineering, retrieval methods, agent architecture, LLM inference APIs & what LLMs preform best in specific tasks (e.g. Gemini for multimodal).Strong coding skills in Python or TypeScript, ideally both.Strong written and oral communication skills, with the ability to explain technical concepts clearly and concisely to both technical and non-technical stakeholders.Startup DNA. The ability to thrive in a fast-moving environment. Views unstructured environments as an opportunity to figure out the most impactful work and help drive he future success of the company.A naturally curious person, always interested in learning new skills and growing as an engineer.Nice to Have:Expertise in LangChain/LangGraph.Experience in Applied AI research roles.Experience building full-stack applications end-to-end, including both design/frontend & backend implementation.Processionally proficient in both Python and TypeScript.Experience maintaining open-source projects.

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Company Overview At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments. This will require close collaboration with our robotics, research, and engineering team. Your work will directly impact the development of intelligent, adaptable robots capable of learning and performing complex tasks autonomously. Responsibilities Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications. Design and conduct experiments to train RL models and conduct real-world tests. Collaborate closely with researchers to explore novel methods of scaling up reinforcement learning model training. Communicate effectively with inference, application, and deployment engineers to integrate RL models into robotic systems and iterate on methods to enable robust deployment. Analyze and interpret experimental results, iterating on model design to achieve desired performance. Stay up-to-date with the latest research and advancements in reinforcement learning. Preferred Qualifications BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience. Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc. Deep understanding and practical experience with various reinforcement learning algorithms and techniques (model-free, model-based, multi-task, hierarchical, multi-agent, etc.). Strong background in algorithms, data structures, and software engineering principles. Experience with physics simulation engines and tools for training RL. Deep understanding of state-of-the-art machine learning techniques and models. Extensive industry experience with reinforcement learning and robotic systems.  Base Salary Range$100,000—$300,000 USD

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At Replicant, we believe AI should work for people, starting with customer service. That’s why we built a platform that helps contact centers resolve more requests, proactively identify issues, and improve agent performance with AI-powered conversation intelligence and AI agents that act like your best reps.Our AI agents handle millions of calls every month for Fortune 500 companies and high-growth innovators. From processing payments to booking appointments and authenticating users, they help customers get what they need instantly, 24/7. Meanwhile, our real-time conversation insights help contact center leaders coach better and improve every interaction.We’re leading the shift from legacy systems to AI-first service, powered by large language models (LLMs)and designed for enterprise scale, security, and empathy. If you’re excited by the potential of LLMs, voice AI, and building category-defining technology with a kind, ambitious team, you’ll love it here.The Machine Learning team empowers enterprise customers and developers on Replicant’s platform to help create delightful conversations that provide fast and effective resolutions to their clients through contact center automation.  We define and build the next generation of bot building paradigms for complex enterprise customer service and contact center automation scenarios. You will be part of a cross-functional group of engineers that are applying the latest research in Generative AI and NLP - including LLMs and other advancements in research into our core product lines.  What you'll doLeading the exploration and application of Large Language Models and Generative AI, venturing into new areas within these fields Translating the latest research into high-performing systems and models that can be practically applied to enhance user experiences Help set the team's strategic direction, cultivating an environment that encourages innovation and professional growthActively engaging in all aspects of development, from ideation and experimentation to implementation and deploymentCollaborating with various teams and product managers to develop and implement ML based solutions, ensuring performance optimization and alignment with broader business goalsWhat you'll bring5+ years of software development experience in ML infra, ML tooling, or products with ML usagePreferred if experienced with the ML ecosystem (e.g. python, pytorch, faiss, elastic search)Excellent communication skills and a vivid imaginationPassion about engineering and team cultureYou love tackling ambiguous technical problems and developing solutions to problems with significant impactYou are an independent thinker and like to own and solve complex problemsYou are interested in exploring the nuance and aesthetic of conversations#LI-RemoteFor all full-time employees, we offer:🏠  Remote working environment that respects time zone differences💸  Highly competitive salaries, equity, and for US Employees, a 401(k) plan🏥  Top of the line healthcare (medical, vision, and dental)🏋️  Health and Wellness Perk🖥️ Equipment Stipend🌴  Flexible vacation policy✈️  Amazing team trips & offsites where you can find our CEO baking bread for the team🌺 Replicants are eligible for a 5-week sabbatical after being at the company for 4.5 yearsOur ValuesReplicant has three core values. It is critical that everyone who joins the team feels excited and moved by these values as every new team member makes an impact on our culture.Blade Runners: We take ownership and pride to influence the outcomes of our goals. We are successful, and like a Blade Runner, use the tools at our disposal to reach our objectives. We value open and honest communication and proactively seek feedback along the way. We are a company driven to grow and achieve both individually and as a team.Bread Makers: We are humble and strive toward an egalitarian culture. No task is too big or too small. We work together to achieve our goals and develop our company mission. We believe that the whole is greater than the sum of its parts in everything that we do.Självdistans (Self-Distance): Självdistans is Swedish for self-distance. It's the ability to critically reflect on oneself and one's relations from an external perspective. With this in mind, we act with objectivity and always remember that we are not our work. There's no perfect science to growing a team or business, but we trust everyone at Replicant to point out our blind spots and humbly admit their own.Replicant is proud to be an equal opportunity employer. We are committed to fostering an inclusive, diverse and equitable workplace that is built on trust, support and respect. We welcome all individuals and do not discriminate on the basis of gender identity and expression, race, ethnicity, disability, sexual orientation, colour, religion, creed, gender, national origin, age, marital status, pregnancy, sex, citizenship, education, languages spoken or veteran status. Accommodation is available upon request at any point during our recruitment process. If you require an accommodation, please speak to your talent acquisition partner or email us at talent@replicant.ai and we’ll work to meet your needs.