Top Machine Learning Engineer Jobs Openings in 2025

false

Mirage is the leading AI short-form video company. We’re building full-stack foundation models and products that redefine video creation, production and editing. Over 20 million creators and businesses use Mirage’s products to reach their full creative and commercial potential.We are a rapidly growing team of ambitious, experienced, and devoted engineers, researchers, designers, marketers, and operators based in NYC. As an early member of our team, you’ll have an opportunity to have an outsized impact on our products and our company's culture.Our ProductsCaptions Mirage Studio Our TechnologyAI Research @ MirageMirage Model AnnouncementSeeing Voices (white-paper)Press CoverageTechCrunchLenny’s PodcastForbes AI 50Fast CompanyOur InvestorsWe’re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more.** Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) We do not work with third-party recruiting agencies, please do not contact us** About the Role and Team:Captions seeks an exceptional Research Engineer (MOTS) to drive innovation in training data infrastructure. You'll conduct research on and develop sophisticated distributed training workflows and optimized data processing systems for massive video and multimodal datasets. Beyond pure performance, you'll develop deep insight into our data to maximize training effectiveness. As an early member of our ML Research team, you'll build foundational systems that directly impact our ability to train models powering video and multimodal creation for millions of users.You'll work directly alongside our research and engineering teams in our NYC office. We've intentionally built a culture where infrastructure and data work is highly valued - your success will be measured by the reliability and performance of our systems, not by your ability to navigate politics. We're a team that loves diving deep into technical problems and emerging with practical solutions.Our team values:Quick iteration and practical solutions.Open discussion of technical approaches.Direct access to decision makers.Regular sharing of learnings, results, and iterative work.Key Responsibilities:Infrastructure Development:Build performant pipelines for processing video and multimodal training data at scale.Design distributed systems that scale seamlessly with our rapidly growing video and multimodal datasets.Create efficient data loading systems optimized for GPU training throughput.Implement comprehensive telemetry for video processing and training pipelines.Core Systems Development:Create foundation data processing systems that intelligently cache and reuse expensive computations across the training pipeline.Build robust data validation and quality measurement systems for video and multimodal content.Design systems for data versioning and reproducing complex multimodal training runs.Develop efficient storage and compute patterns for high-dimensional data and learned representations.System Optimization:Own and improve end-to-end training pipeline performance.Build systems for efficient storage and retrieval of video training data.Build frameworks for systematic data and model quality improvement.Develop infrastructure supporting fast research iteration cycles.Build tools and systems for deep understanding of our training data characteristics.Research & Product Impact:Build infrastructure enabling rapid testing of research hypotheses.Create systems for incorporating user feedback into training workflows.Design measurement frameworks that connect model improvements to user outcomes.Enable systematic experimentation with direct user feedback loops.Requirements: Technical Background:Bachelor's or Master's degree in Computer Science, Machine Learning, or related field.3+ years experience in ML infrastructure development or large-scale data engineering.Strong programming skills, particularly in Python and distributed computing frameworks.Expertise in building and optimizing high-throughput data pipelines.Proven experience with video/image data pre-processing and feature engineering.Deep knowledge of machine learning workflows, including model training and data loading systems.System Development:Track record in performance optimization and system scaling.Experience with cluster management and distributed computing.Background in MLOps and infrastructure monitoring.Demonstrated ability to build reliable, large-scale data processing systems.Engineering Approach:Love tackling hard technical problems head-on.Take ownership while knowing when to loop in teammates.Get excited about improving system performance.Want to work directly with researchers and engineers who are equally passionate about building great systems.Benefits:Comprehensive medical, dental, and vision plans401K with employer matchCommuter BenefitsCatered lunch multiple days per weekDinner stipend every night if you're working late and want a bite! Grubhub subscriptionHealth & Wellness Perks (Talkspace, Kindbody, One Medical subscription, HealthAdvocate, Teladoc)Multiple team offsites per year with team events every monthGenerous PTO policyCaptions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.Please note benefits apply to full time employees only.

false

Mirage is the leading AI short-form video company. We’re building full-stack foundation models and products that redefine video creation, production and editing. Over 20 million creators and businesses use Mirage’s products to reach their full creative and commercial potential.We are a rapidly growing team of ambitious, experienced, and devoted engineers, researchers, designers, marketers, and operators based in NYC. As an early member of our team, you’ll have an opportunity to have an outsized impact on our products and our company's culture.Our ProductsCaptions Mirage Studio Our TechnologyAI Research @ MirageMirage Model AnnouncementSeeing Voices (white-paper)Press CoverageTechCrunchLenny’s PodcastForbes AI 50Fast CompanyOur InvestorsWe’re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more.** Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) We do not work with third-party recruiting agencies, please do not contact us** About the role: Captions is seeking a Machine Learning Engineer to partner closely with our Researchers and bring large-scale multimodal video diffusion models into production. You’ll be responsible for optimizing and deploying state-of-the-art generative models (tens to hundreds of billions of parameters) to deliver low-latency, high-throughput inference at scale. This is a unique opportunity to work on cutting-edge AI—spanning audio-video generation, diffusion architectures, and temporal modeling—and ensure these innovations reach millions of creators worldwide. Responsibilities:Inference & DeploymentDevelop high-performance GPU-based inference pipelines for large multimodal diffusion models.Build, optimize, and maintain serving infrastructure to deliver low-latency predictions at large scale.Collaborate with DevOps teams to containerize models, manage autoscaling, and ensure uptime SLAs.Model Optimization & Fine-TuningLeverage techniques like quantization, pruning, and distillation to reduce latency and memory footprint without compromising quality.Implement continuous fine-tuning workflows to adapt models based on real-world data and feedback.Production MLOpsDesign and maintain automated CI/CD pipelines for model deployment, versioning, and rollback.Implement robust monitoring (latency, throughput, concept drift) and alerting for critical production systems.Performance & ScalingExplore cutting-edge GPU acceleration frameworks (e.g., TensorRT, Triton, TorchServe) to continuously improve throughput and reduce costs.Requirements: Technical ExpertiseProven experience deploying deep learning models on GPU-based infrastructure (NVIDIA GPUs, CUDA, TensorRT, etc.).Strong knowledge of containerization (Docker, Kubernetes) and microservice architectures for ML model serving.Proficiency with Python and at least one deep learning framework (PyTorch, TensorFlow).Model Optimization Familiarity with compression techniques (quantization, pruning, distillation) for large-scale models.Experience profiling and optimizing model inference (batching, concurrency, hardware utilization).InfrastructureHands-on experience with ML pipeline orchestration (Airflow, Kubeflow, Argo) and automated CI/CD for ML.Strong grasp of logging, monitoring, and alerting tools (Prometheus, Grafana, etc.) in distributed systems.Domain ExperienceExposure to diffusion models, multimodal video generation, or large-scale generative architectures.Experience with distributed training frameworks (FSDP, DeepSpeed, Megatron-LM) or HPC environments.Benefits:Comprehensive medical, dental, and vision plans401K with employer matchCommuter BenefitsCatered lunch multiple days per weekDinner stipend every night if you're working late and want a bite! Grubhub subscriptionHealth & Wellness Perks (Talkspace, Kindbody, One Medical subscription, HealthAdvocate, Teladoc)Multiple team offsites per year with team events every monthGenerous PTO policyCaptions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.Please note benefits apply to full time employees only.

false

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading.About the team + role We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The mission of the AI Research and Development team is to provide scalable data and model driven decision making solutions to the various business functions at Robinhood.  We aim to create a personalized experience for our users, by helping them discover & engage with the right products & features within Robinhood that they might find most valuable.  To accelerate progress, we are also building an accessible model development platform to democratize machine learning practices throughout the company.  As we embark on this exciting journey, we are looking for a Senior Machine Learning Engineer to join us to make this vision a reality. This role is based in our Menlo Park, CA or Bellevue, WA office(s), with in-person attendance expected at least 3 days per week.  At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. What you'll do As a Machine Learning Engineer on our team, your primary focus will be on the implementation and evaluation of machine learning algorithms through rigorous experimentation and testing methodologies. Your responsibilities will include: Model Development and Implementation: Develop and implement scalable machine learning models focusing on advanced ranking and recommendation systems, including expertise in Collaborative Filtering, Content-Based Filtering, and Hybrid models, alongside proficiency in Learning to Rank (LTR) techniques for effective prioritization. Additionally, design reinforcement learning algorithms and apply multi-armed bandit strategies to optimize decision-making in dynamic environments, balancing exploration and exploitation. A/B Testing and Experimentation: Design and conduct A/B tests to assess the performance of different machine learning models. This includes setting up the test environment, monitoring performance, and analyzing results. Data Analysis and Insight Generation: Analyze experimental data to extract actionable insights. Use statistical techniques to validate the findings and ensure their relevance and accuracy. Cross-Functional Collaboration: Work closely with other engineering teams, data scientists, and the marketing team to integrate machine learning models into the product and ensure they meet business requirements.  Present results to different stakeholders. Tooling and Documentation: Build reusable libraries for common machine learning practices.  Offer support and guidance to the usage of these tools.  Maintain comprehensive documentation of libraries, models, experiments, and findings. . What you bring 2+ years of applied ML experience productionizing ML models with a focus on recommendations, ranking or personalization projects. A fervent interest in exploring and applying AI and ML technologies. Strive to solve sophisticated engineering problems that drive business objectives. Solid technical foundation enabling active contribution to the design and execution of projects and ideas. Familiarity with architectural frameworks of large, distributed, and high-scale ML applications. Proven experience in ML with a focus on ranking, recommendation systems, multi-objective optimization, and reinforcement learning. Proficiency in Python, SQL, XGboost, PyTorch/TensorFlow. Experience with Spark, Kafka, and Kubernetes is also desirable. What we offer Challenging, high-impact work to grow your career Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching Best in class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more Employer-paid life & disability insurance, fertility benefits, and mental health benefits Time off to recharge including company holidays, paid time off, sick time, parental leave, and more! Exceptional office experience with catered meals, events, and comfortable workspaces. In addition to the base pay range listed below, this role is also eligible for bonus opportunities + equity + benefits. Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands. The expected base pay range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones. For other locations not listed, compensation can be discussed with your recruiter during the interview process. Base Pay Range:Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC)$157,000—$185,000 USDZone 2 (Denver, CO; Westlake, TX; Chicago, IL)$139,000—$163,000 USDZone 3 (Lake Mary, FL; Clearwater, FL; Gainesville, FL)$122,000—$144,000 USDClick here to learn more about our Total Rewards, which vary by region and entity. If our mission energizes you and you’re ready to build the future of finance, we look forward to seeing your application. Robinhood provides equal opportunity for all applicants, offers reasonable accommodations upon request, and complies with applicable equal employment and privacy laws. Inclusion is built into how we hire and work—welcoming different backgrounds, perspectives, and experiences so everyone can do their best. Please review the Privacy Policy for your country of application.

false

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 Applied Scientists and Research Engineers focused on multimodal learning (text, image, audio, video) to drive innovative research and collaborate with clients on complex projects.You will design, train, and deploy SOTA multimodal models (e.g., Omni-models, VLMs, Audio, Image generation, Robotics and much more) and apply them to diverse use cases: enterprise search, agents grounded in images and documents, video understanding, and speech interfaces. You’ll work cross‑functionally with internal and external science, engineering, and product teams to deliver high‑impact AI solutions. What you will do • Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs. You don’t panic when you see OOM errors or when NCCL feels like not wanting to talk.• Generate and curate multimodal datasets (web‑scale image‑text, document‑image, audio‑text, video‑text), and build robust evaluators/benchmarks for perception, grounding, OCR, and captioning.• Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment.• Collaborate with cross-functional teams to tackle complex use cases using agents and RAG pipelines.• Manage research projects and communications with client research teams. About you • You are fluent in English, and have excellent communication skills. You are at ease explaining complex technical concepts to both technical and non-technical audiences.• You’re an expert with PyTorch or JAX.• You’re not afraid of contributing to a big codebase and can find yourself around independently with little guidance.• You have experience in one of the following: VLMs, diffusion for image/video, audio processing (ASR/TTS), image processing, robotics.• You write clean, readable, high-performance, fault-tolerant Python code.• You don’t need roadmaps: you just do. You don’t need a manager: you just ship.• Low-ego, collaborative and eager to learn.• You have a track record of success through personal projects, professional projects or in academia. It would be great if you • Hold a PhD / master in a relevant field (e.g., Mathematics, Physics, Machine Learning), but if you’re an exceptional candidate from a different background, you should apply.• Can bring a variety of research experience (agents, multi-modality, robotics, diffusion, time-series).• Have contributed to a large codebase used by many (open source or in the industry).• Have a track record of publications in top academic journals or conferences.• Love improving existing code by fixing typing issues, adding tests and improving CI pipelines. Benefits We have local offices in Paris, London, Marseille, Singapore and Palo Alto. 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)

false

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 Applied Scientists and Research Engineers to build telemetry-native security agents and specialized foundation models for observability and defense. You’ll create agents that detect, diagnose, and help resolve incidents—grounded in real-world security and SRE workflows—and evaluate them in simulated environments before hardening for production.You’ll work across model research, large-scale training, and productization with a strong emphasis on provenance, auditability, and safety. What you will do • Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs. You don’t panic when you see OOM errors or when NCCL feels like not wanting to talk.• Develop and pre-/post-train domain-specialized foundation models for observability, security, site reliability engineering, and code repair• Run large‑scale experiments to balance accuracy, latency, throughput, and power under tight memory constraints; profile and fix bandwidth/compute bottlenecks.• Manage research projects and communications with client research teams. About you • You are fluent in English, and have excellent communication skills. You are at ease explaining complex technical concepts to both technical and non-technical audiences.• You have background in adversarial ML, agent/prompt security, watermarking/detectors, differential privacy, or trusted execution (TEE).• You’re not afraid of contributing to a big codebase and can find yourself around independently with little guidance.• You’re expert with PyTorch or JAX; strong C++/CUDA or low‑level performance skills a plus; production‑grade Python.• You don’t need roadmaps: you just do. You don’t need a manager: you just ship.• Low-ego, collaborative and eager to learn.• You have a track record of success through personal projects, professional projects or in academia. It would be great if you • Hold a PhD / master in a relevant field (e.g., Mathematics, Physics, Machine Learning), but if you’re an exceptional candidate from a different background, you should apply.• Have contributed to a large codebase used by many (open source or in the industry).• Have a track record of publications in top academic journals or conferences.• Have publications in top ML/security venues and/or contributions to open-source security or observability tools.• Love improving existing code by fixing typing issues, adding tests and improving CI pipelines. Benefits We have local offices in Paris, London, Marseille, Singapore and Palo Alto. 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)

false

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 Applied Scientists and Research Engineers focused on model efficiency and edge deployment. You will research and build ultra‑efficient models and toolchains for on‑device inference across CPUs, GPUs, NPUs, and specialized accelerators. Your work will enable Mistral models to run privately, reliably, and fast on mobile, desktop, and embedded devices. What you will do • Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs. You don’t panic when you see OOM errors or when NCCL feels like not wanting to talk.• Design and evaluate quantization, pruning, distillation, and sparsity methods for LLMs and multimodal models.• Build deployment stacks, optimize kernels and memory layouts.• Run large‑scale experiments to balance accuracy, latency, throughput, and power under tight memory constraints; profile and fix bandwidth/compute bottlenecks.• Develop tooling for calibration data generation, mixed‑precision training, quant‑aware finetuning, structured/unstructured sparsity, and compilation passes.• Manage research projects and communications with client research teams. About you • You are fluent in English, and have excellent communication skills. You are at ease explaining complex technical concepts to both technical and non-technical audiences.• You’re not afraid of contributing to a big codebase and can find yourself around independently with little guidance.• You’ve a deep understanding of quantization trade‑offs, hardware constraints, and compiler stacks• You’re expert with PyTorch or JAX; strong C++/CUDA or low‑level performance skills a plus; production‑grade Python.• You don’t need roadmaps: you just do. You don’t need a manager: you just ship.• Low-ego, collaborative and eager to learn.• You have a track record of success through personal projects, professional projects or in academia. It would be great if you • Hold a PhD / master in a relevant field (e.g., Mathematics, Physics, Machine Learning), but if you’re an exceptional candidate from a different background, you should apply.• Have contributed to a large codebase used by many (open source or in the industry).• Have a track record of publications in top academic journals or conferences.• Contributions to open‑source inference/compilers stacks.• Love improving existing code by fixing typing issues, adding tests and improving CI pipelines.• Have experience optimizing inference on edge devices Benefits We have local offices in Paris, London, Marseille, Singapore and Palo Alto. 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)

false

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 Applied Scientists and Research Engineers specializing in time‑series modeling to build SOTA forecasting, detection, and control systems across domains such as finance, energy, IoT, healthcare, and operations. You will design foundation‑style temporal models and hybrids (LLM + TS), and deploy them in latency‑sensitive, reliability‑critical environments. You’ll partner with clients to translate raw telemetry into actionable insights. What you will do • Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs. You don’t panic when you see OOM errors or when NCCL feels like not wanting to talk.• Pre‑train and fine‑tune time series foundational models for downstream applications in various industries• Generate and curate data for pre-training and post-training, working on evaluations and making sure the model’s performance beats expectations.• Manage research projects and communications with client research teams. About you • You are fluent in English, and have excellent communication skills. You are at ease explaining complex technical concepts to both technical and non-technical audiences.• You’re an expert with PyTorch or JAX.• You’re not afraid of contributing to a big codebase and can find yourself around independently with little guidance.• You write clean, readable, high-performance, fault-tolerant Python code.• You don’t need roadmaps: you just do. You don’t need a manager: you just ship.• Low-ego, collaborative and eager to learn.• You have a track record of success through personal projects, professional projects or in academia.• Proven work with time‑series modeling and transformers models applied to time-series: forecasting, anomaly/change‑point detection, irregular sampling, multivariate and hierarchical series. It would be great if you • Hold a PhD / master in a relevant field (e.g., Mathematics, Physics, Machine Learning), but if you’re an exceptional candidate from a different background, you should apply.• Have contributed to a large codebase used by many (open source or in the industry).• Have a track record of publications in top academic journals or conferences.• Love improving existing code by fixing typing issues, adding tests and improving CI pipelines. Benefits We have local offices in Paris, London, Marseille, Singapore and Palo Alto. 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)

false

We’re looking for an Applied Machine Learning Engineer to design and deploy intelligent systems to automate infrastructure workflows. You’ll work hands-on with cutting-edge technologies—LLMs, knowledge graphs, and advanced retrieval systems—to build scalable, agentic systems. You’ll rapidly prototype, experiment, and take projects from concept to production. If you thrive in fast-paced environments and are passionate about applied AI, this is the role for you.About AntimetalAntimetal is building the future of infrastructure management. We're starting by creating a platform that investigates, resolves, and prevents issues—giving engineers their time back to focus on what they do best: building great products.What you bring:At least 5 years of experience in applied machine learning or a related role, preferably at a high-growth companyDemonstrated ability to design and deploy large-scale machine learning systems that add new value to the product.Strong on ML fundamentals: classification/regression, clustering, dimensionality reduction, evaluation & error analysis, probabilistic MLReal world expertise in one area of applied ML: search, statistical modeling, NLP, etc.Experience constructing and running end-to-end evaluation pipelines with real world data.Proficient in Python and Typescript, with experience using common ML libraries and data engineering tools.Strong problem-solving skills, with a focus on creating highly maintainable, scalable code.Excellent communication and collaboration skills.Comfortable with iterative development, prototyping, and adapting quickly to feedback.Bonus:Hands-on experience with vector/hybrid search.Experience with dataset curation or synthetic dataset generation for novel problem domains.A passion for staying ahead of applied AI trends and prototyping emerging technologies.Contributions to open-source ML tools or libraries.Experience with Go or another systems language.Who you are:Identify as a builderAre excited to work in-person from our new and spacious office in New YorkLove working in a startup environment (experience in a startup or obsession with going zero-to-one)Enjoy working with people who are ambitious, caring, and think in systemsThrive in a fast-paced iterative environment where experimentation is essentialWhat we bring:Pay & ownership — Competitive salary with generous equity grants.Full coverage + retirement — Fully covered health, dental, and vision, plus retirement benefits.Unlimited PTO — Take the time you need to recharge.Dinner on late nights — Working late? Dinner is on us.Fitness stipend — Monthly support for your health and wellness.Tools of the trade — Any equipment you need to do your best work.Commute perks — Citi Bike + train benefits.Interview processApplication Review – Send us your stuff, and a quick note on why you're excited.Intro Chat: Share what you're looking for next and learn more about what we're building.Founder Interview: Talk with one of our founders in more detail about the roleTechnical Interview: We’ll have you complete a short exercise specific to the role.Onsite: Come onsite and meet the team through a series of 1:1 interviews.Decision – We’ll move fast.

false

About H: H exists to push the boundaries of superintelligence with agentic AI. By automating complex, multi-step tasks typically performed by humans, AI agents will help unlock full human potential.H is hiring the world’s best AI talent, seeking those who are dedicated as much to building safely and responsibly as to advancing disruptive agentic capabilities. We promote a mindset of openness, learning, and collaboration, where everyone has something to contribute. About the Team: The Inference team develops and enhances the inference stack for serving H-models that power our agent technology. The team focuses on optimizing hardware utilization to reach high throughput, low latency and cost efficiency in order to deliver a seamless user experience. Key Responsibilities:Develop scalable, low-latency and cost effective inference pipelinesOptimize model performance: memory usage, throughput, and latency, using advanced techniques like distributed computing, model compression, quantization and caching mechanismsDevelop specialized GPU kernels for performance-critical tasks like attention mechanisms, matrix multiplications, etc.Collaborate with H research teams on model architectures to enhance efficiency during inferenceReview state-of-the-art papers to improve memory usage, throughput and latency (Flash attention, Paged Attention, Continuous batching, etc.)Prioritize and implement state-of-the-art inference techniquesRequirements:Technical skills:MS or PhD in Computer Science, Machine Learning or related fieldsProficient in at least one of the following programming languages: Python, Rust or C/C++Experience in GPU programming such as CUDA, Open AI Triton, Metal, etc.Experience in model compression and quantization techniquesSoft skillsCollaborative mindset, thriving in dynamic, multidisciplinary teamsStrong communication and presentation skillsEager to explore new challenges Bonuses:Experience with LLM serving frameworks such as vLLM, TensorRT-LLM, SGLang, llama.cpp, etc.Experience with CUDA kernel programming and NCCLExperience in deep learning inference framework (Pytorch/execuTorch, ONNX Runtime, GGML, etc.)Location: Paris or London.This role is hybrid, and you are expected to be in the office 3 days a week on average.The final decision for this will lie with the hiring manager for each individual roleWhat We Offer:Join the exciting journey of shaping the future of AI, and be part of the early days of one of the hottest AI startupsCollaborate with a fun, dynamic and multicultural team, working alongside world-class AI talent in a highly collaborative environmentEnjoy a competitive salaryUnlock opportunities for professional growth, continuous learning, and career developmentIf you want to change the status quo in AI, join us.

false

About UsHippocratic AI has developed a safety-focused Large Language Model (LLM) for healthcare. The company believes that a safe LLM can dramatically improve healthcare accessibility and health outcomes in the world by bringing deep healthcare expertise to every human. No other technology has the potential to have this level of global impact on health.Why Join Our TeamInnovative Mission: We are developing a safe, healthcare-focused large language model (LLM) designed to revolutionize health outcomes on a global scale.Visionary Leadership: Hippocratic AI was co-founded by CEO Munjal Shah, alongside a group of physicians, hospital administrators, healthcare professionals, and artificial intelligence researchers from leading institutions, including El Camino Health, Johns Hopkins, Stanford, Microsoft, Google, and NVIDIA.Strategic Investors: We have raised a total of $278 million in funding, backed by top investors such as Andreessen Horowitz, General Catalyst, Kleiner Perkins, NVIDIA’s NVentures, Premji Invest, SV Angel, and six health systems.World-Class Team: Our team is composed of leading experts in healthcare and artificial intelligence, ensuring our technology is safe, effective, and capable of delivering meaningful improvements to healthcare delivery and outcomes.For more information, visit www.HippocraticAI.com.Location Requirement:This is a Palo Alto–based role and requires working onsite five days a week. Only candidates who are currently local or willing to relocate will be consideredAbout the RoleHippocratic AI is building safety‑first generative intelligence for healthcare. We are hiring an RN with clinical product experience to partner with our model and product teams to develop, validate, and continuously improve our medical large language models (LLMs). This role sits at the intersection of clinical expertise, patient communication, and product innovation – ensuring our AI agents are accurate, empathetic, and aligned with clinical best practices. What You’ll DoEvaluate the Medical Model. Design and run clinical evaluation protocols to assess the accuracy, safety, and appropriateness against guidelines and standards of care.Provide Clinical Insights. Translate frontline nursing expertise into product decisions—shaping dialog flows, safety rails, escalation criteria, and patient‑friendly explanations.Review & Triage Errors. Analyze error reports, identify root causes, and partner with engineers/researchers on remediation plans.Author “Gold Standards.” Create test cases, rubrics, and reference answers for high‑stakes scenarios; define acceptance criteria for model releases.Cross‑Functional Partner. Collaborate with ML researchers, speech/voice specialists, product managers, and QA to prioritize improvements and measure impact.What You Bring:Must-Have:Active, unrestricted Nursing License (RN) in your practicing state.Clinical experience in acute, ambulatory, telehealth, or community settings; strong patient communication skills.Excellent written & verbal communication—ability to explain complex medical concepts clearly to lay audiences and to technical teams.Prior experience with prompting language models, interacting or working with LLMs via text or voice, conversational AI, or clinical NLP. Commitment to safety and ethics; familiarity with HIPAA/PHI handling and privacy best practices.Intellectual curiosity and a commitment to advance health delivery and increase access to all.Nice‑to‑Have:Background in quality/safety or clinical education.Experience with clinical guidelines and patient‑education best practices.Domain expertise in clinical and care management workflows.***Be aware of recruitment scams impersonating Hippocratic AI. All recruiting communication will come from @hippocraticai.com email addresses. We will never request payment or sensitive personal information during the hiring process. If anything

true

Who We Are At RelationalAI, we are building the future of intelligent data systems through our cloud-native relational knowledge graph management system—a platform designed for learning, reasoning, and prediction. We are a remote-first, globally distributed team with colleagues across six continents. From day one, we’ve embraced asynchronous collaboration and flexible schedules, recognizing that innovation doesn’t follow a 9-to-5. We are committed to an open, transparent, and inclusive workplace. We value the unique backgrounds of every team member and believe in fostering a culture of respect, curiosity, and innovation. We support each other’s growth and success—and take the well-being of our colleagues seriously. We encourage everyone to find a healthy balance that affords them a productive, happy life, wherever they choose to live. We bring together engineers who love building core infrastructure, obsess over developer experience, and want to make complex systems scalable, observable, and reliable.Machine Learning Systems Engineer  Location: Remote (San Francisco Bay Area / North America / South America) Experience Level: 3+ years of experience in machine learning engineering or research About ScalarLM This role will involve heavily working with the ScalarLM framework and team. ScalarLM unifies vLLM, Megatron-LM, and HuggingFace for fast LLM training, inference, and self-improving agents—all via an OpenAI-compatible interface. ScalarLM builds on top of the vLLM inference engine, the Megatron-LM training framework, and the HuggingFace model hub. It unifies the capabilities of these tools into a single platform, enabling users to easily perform LLM inference and training, and build higher lever applications such as Agents with a twist - they can teach themselves new abilities via back propagation. ScalarLM is inspired by the work of Seymour Roger Cray (September 28, 1925 – October 5, 1996), an American electrical engineer and supercomputer architect who designed a series of computers that were the fastest in the world for decades, and founded Cray Research, which built many of these machines. Called "the father of supercomputing", Cray has been credited with creating the supercomputer industry. It is a fully open source project (CC-0 Licensed) focused on democratizing access to cutting-edge LLM infrastructure that combines training and inference in a unified platform, enabling the development of self-improving AI agents similar to DeepSeek R1. ScalarLM is supported and maintained by TensorWave in addition to RelationalAI. The Role: As a Machine Learning Engineer, you will contribute directly to our machine learning infrastructure, to the ScalarLM open source codebase, and build large-scale language model applications on top of it. You’ll operate at the intersection of high-performance computing, distributed systems, and cutting-edge machine learning research, developing the fundamental infrastructure that enables researchers and organizations worldwide to train and deploy large language models at scale. This is an opportunity to take on technically demanding projects, contribute to foundational systems, and help shape the next generation of intelligent computing. You Will:  Contribute code and performance improvements to the open source project. Develop and optimize distributed training algorithms for large language models. Implement high-performance inference engines and optimization techniques. Work on integration between vLLM, Megatron-LM, and HuggingFace ecosystems. Build tools for seamless model training, fine-tuning, and deployment. Optimize performance of advanced GPU architectures. Collaborate with the open source community on feature development and bug fixes. Research and implement new techniques for self-improving AI agents. Who You Are Technical Skills: Programming Languages: Proficiency in both C/C++ and Python High Performance Computing: Deep understanding of HPC concepts, including: MPI (Message Passing Interface) programming and optimization Bulk Synchronous Parallel (BSP) computing models Multi-GPU and multi-node distributed computing CUDA/ROCm programming experience preferred Machine Learning Foundations: Solid understanding of gradient descent and backpropagation algorithms Experience with transformer architectures and the ability to explain their mechanics Knowledge of deep learning training and its applications Understanding of distributed training techniques (data parallelism, model parallelism, pipeline parallelism, large batch training, optimization) Research and Development  Publications: Experience with machine learning research and publications preferred Research Skills: Ability to read, understand, and implement techniques from recent ML research papers Open Source: Demonstrated commitment to open source development and community collaboration Experience 3+ years of experience in machine learning engineering or research. Experience with large-scale distributed training frameworks (Megatron-LM, DeepSpeed, FairScale, etc.). Familiarity with inference optimization frameworks (vLLM, TensorRT, etc.). Experience with containerization (Docker, Kubernetes) and cluster management. Background in systems programming and performance optimization. Bonus points if: PhD or MS in Computer Science, Computer Engineering, Machine Learning, or related field. Experience with SLURM, Kubernetes, or other cluster orchestration systems. Knowledge of mixed precision training, data parallel training, and scaling laws. Experience with transformer architecture, pytorch, decoding algorithms. Familiarity with high performance GPU programming ecosystem.  Previous contributions to major open source ML projects. Experience with MLOps and model deployment at scale. Understanding of modern attention mechanisms (multi-head attention, grouped query attention, etc.). Why RelationalAI RelationalAI is committed to an open, transparent, and inclusive workplace. We value the unique backgrounds of our team. We are driven by curiosity, value innovation, and help each other to succeed and to grow. We take the well-being of our colleagues seriously, and offer flexible working hours so each individual can find a healthy balance that affords them a productive, happy life wherever they choose to live. 🌎 Global Benefits at RelationalAI At RelationalAI, we believe that people do their best work when they feel supported, empowered, and balanced. Our benefits prioritize well-being, flexibility, and growth, ensuring you have the resources to thrive both professionally and personally. We are all owners in the company and reward you with a competitive salary and equity. Work from anywhere in the world. Comprehensive benefits coverage, including global mental health support Open PTO – Take the time you need, when you need it. Company Holidays, Your Regional Holidays, and RAI Holidays—where we take one Monday off each month, followed by a week without recurring meetings, giving you the time and space to recharge. Paid parental leave – Supporting new parents as they grow their families. We invest in your learning & development Regular team offsites and global events – Building strong connections while working remotely through team offsites and global events that bring everyone together. A culture of transparency & knowledge-sharing – Open communication through team standups, fireside chats, and open meetings. Country Hiring Guidelines: RelationalAI hires around the world. All of our roles are remote; however, some locations might carry specific eligibility requirements. Because of this, understanding location & visa support helps us better prepare to onboard our colleagues. Our People Operations team can help answer any questions about location after starting the recruitment process.   Privacy Policy: EU residents applying for positions at RelationalAI can see our Privacy Policy here. California residents applying for positions at RelationalAI can see our Privacy Policy here   RelationalAI is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, color, gender identity or expression, marital status, national origin, disability, protected veteran status, race, religion, pregnancy, sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.

true

Robyn is not just an AI app — she’s your emotionally intelligent companion. A trusted mirror. A guide. A new kind of OS for your emotional life.We're building the world’s first emotional intelligence layer for AI.You’ll be building the backend infrastructure that powers all of it:Conversations, memory, and real-time personalizationVoice + chat interfaceScalable infra for emotional intelligenceSecure and fast APIs for our iOS appA robust ML inference and fine-tuning pipelineYou’ll be the technical backbone of Robyn — designing and shipping fast, scalable, emotionally aware systems while collaborating closely with iOS, product, and AI teams.This is a rare opportunity to define the foundations of emotionally intelligent AI. Everything beyond the core LLM — memory, emotional layer, and relational engine — is built fully in-house. The backend engineer will help architect the systems that make Robyn feel human: writing the foundational codebase for the next wave of AI — one that feels, remembers, and connects.What You'll DoBackend & Infra OwnershipYou'll work and add to our C# / .NET / ASP.NET backend api layer (have experience in this or something similar like Java/Spring and can learn quickly) and progressively add many Python microservices (FastAPI or AWS Lambda) with modular, AI-native architecture in mind to build our intelligence layer. Deploy models and setup some ml training pipelines.Understand dependency injection, Strategy Pattern, inversion of control, and other best practices for code maintainabilityOwn the full backend surface area — auth, APIs, infra, orchestration — and design all of your features for scale and velocity.Build and maintain REST and GraphQL APIs consumed by our iOS client; low-latency, resilient, and well-instrumented.Architect a microservice-style ML model serving backend deployed via Docker containers or AWS Lambda (SnapStart), backed by async eventing and pub/sub where needed.Own CI/CD, rollback strategies, logging, error handling — the backend is your domain, end-to-end.AI & ML Systems IntegrationArchitect and manage existing vector DB (PgVector) and potentially add more to power retrieval-augmented generation, evolving memory, and personalization.Build tools and add to our custom memory pipelines tied to user context, embeddings, and interaction history.Integrate and scale inference with OpenAI, Claude, Llama, or other models. Build wrappers, manage caching, fallbacks, and prompt routing logic.Own emotion and sentiment tagging workflows; plug in APIs or run lightweight classifiers in-line.Maintain API orchestration layer with 3rd party model providers (OpenAI, ElevenLabs, etc.).Cloud Infra, DevOps, and Data StackManage our AWS infrastructure and add to our current stack with new innovate technologies: Lambda, ECS, S3, RDS (Postgres), CloudFront, IAM, Route53 — you’ll be the one making the call on architecture and trade-offs.Be able to use search databases like OpenSearchInfra-as-code with Terraform. Pipelines through GitHub Actions.Full observability: metrics, structured logging, tracing, alerting — Open Telemetry, Sentry, Grafana, Cloudwatch, etc.Optimize latency across API surface, tune Postgres indexes, add Redis caching layers to many of your services and pub/sub or streaming for near-instantaneous data sync.Set up and secure infra for SOC-2 readiness: access controls, data lifecycle policies, encrypted storage.Personalization & Emotional Intelligence LayerDesign and ship emotion-aware backend systems that update in real time based on user behavior.Implement custom memory engines — user embeddings, experience graphs, emotional scores — and build APIs that adapt over time.Work with product and AI to tune behavior of Robyn based on user feedback, emotion logs, memory history, and interaction loops.All personalization logicYou’re Probably Right for This If:You have 6 - 15 years of experience in backend or full-stack development; building 0-1 products or teams in a startup environmentYou’ve shipped entire production backends at high-growth early-stage startups — you know how to move fast and still write code you don’t hate six months later.You’ve integrated or scaled LLM-based products — bonus if you’ve done it with emotion, memory, or personalization layers.You care about systems thinking, fast response times, clean abstractions, and building infra that won’t fall over under load.You’ve done the zero-to-one and can hold both the product in your head and the infra in your hands.You’re able to figure things out quickly and dive in wherever needed. There’s no “that’s not my job” here.You're allergic to bloated teams — you’d rather build it right yourself than manage a swarm of mid devs doing it wrong.

false

Distyl AI develops AI native technologies for humans & AI to collaborate to power the operations of the Global Fortune 1000.In just 24 months, we’ve rapidly grown to partner with some of the world’s largest enterprises—including F100 telecom, healthcare, manufacturing, insurance, and retail companies—delivering multiple AI deployments with $100M+ impact. Our platform, Distillery, along with our team of AI Engineers, Researchers, and Strategists, is pioneering AI-native systems of work, solving the most complex, high-stakes challenges at scale.Distyl is founded and led by proven leaders from companies like Palantir, Apple, and top national laboratories. We work in deep partnership with OpenAI, jointly going-to-market at the largest enterprises and collaborating evaluating and testing the latest models. Backed by Lightspeed, Khosla, Coatue, industry leaders like Nat Friedman (former GitHub CEO), as well as board members of over 20+ F500s, Distyl is building the future of AI-powered enterprise operations.What We Are Looking ForAt Distyl we’re pushing the envelope of AI utilization in enterprise. This requires creative researchers who don’t just want to drive incremental improvements on benchmarks or optimize an existing process but instead are looking to creatively redefine how software is used.Our researchers come from many academic backgrounds but have strong research track records, operate in an AI-native way, and would be bored staying on the rails of a traditional research org.Key ResponsibilitiesThe System Self-Construction team builds systems that can build other systems. Researchers design architectures capable of autonomously generating, assembling, and refining sub-systems. This involves developing meta-learning loops, automated pipeline generation, and self-architecting frameworks that reduce the human bottleneck in complex system creation.Researchers in Self-Construction study recursive design principles: how systems represent their own construction processes, evaluate them, and evolve. They draw from meta-learning, program synthesis, and evolutionary computation to explore what it means for a system to “understand” and redesign itself. Their work defines the frontier of self-referential, generative system architectures.What We RequireExperience Building Modular and Composable Systems: You’ve engineered architectures where components interact dynamically (e.g. graph-based planners, agent orchestration frameworks, workflow engines, or automated pipeline builders).Experience Building with Models, Not Just Building Models: We develop intelligent systems using models rather than training or fine-tuning them. Ideal candidates have expertise in compound AI systems, agentic collaboration, and associated techniques (ensembling, ReAct, graph-of-thoughts, etc.).Proven Track Record of Research Results: Whether you’ve published in top journals, posted amazing work on twitter, or somewhere else we want to see what you've done.Uses AI Every Day: Before you can revolutionize someone else’s workflow, you need to revolutionize yours. You should be using tools like ChatGPT, Cursor, and Perplexity to accelerate your workflow.Strong Programming and Data Analysis Skills: While you might not consider yourself a software engineer you need to be able to build prototypes of your ideas and then perform the experiments to prove the effectiveness to a F500 Head of AI.Biases Towards Showing vs Telling: Our customers want to see the power of AI today vs discuss the most elegant idea that will take 5 years to realize.What We OfferAn opportunity to advance the cutting edge of LLM research and directly revolutionize work in the enterprise space.Ownership of high-impact research projects, with the autonomy to explore novel approaches and solutions.Access to state-of-the-art AI models, real business problems, and proprietary data sets across a diverse range of real-world industries.Competitive salary and benefits package, including equity options, medical/dental/vision covered at 100% for you and your dependents, 401K plan, and perks such as commuter benefits and lunch provided in office. Be part of a mission-oriented company to create practical adoption during the biggest revolution in human productivity.A collaborative and intellectually stimulating environment that encourages innovation and personal growth.If you are an innovative, ambitious, and driven individual looking to make a difference in the world of AI, we want to hear from you. Apply now to join our team as an Applied AI Researcher and help us shape the future of AI-driven solutions for enterprises across the globe.Note: Distyl is a hybrid working environment and requires in office collaboration 3 days a week. We have offices in SF and NYC

false

ABOUT RETELL AIRetell AI is using the first principles to reimagine the call center with cutting edge voice AI.We believe voice is still the most natural way humans communicate, yet it has been trapped in outdated call centers for decades. Our mission is to bring intelligence, empathy, and speed to every phone conversation between businesses and their customers.Since launching 18 months ago, thousands of companies now utilize Retell’s AI voice agents to handle sales, support, and logistics calls that once required large teams of human agents. Backed by Y Combinator, Altman Capital, and other leading investors, we have scaled to $30M ARR with a team of 20 people, up from $5M at the start of 2025.Now, we’re scaling fast, and we’re looking for bold, ambitious people to help us build the gold standard for voice automation. If you want to work on deeply technical challenges, move fast, and make an outsized impact at one of the fastest-growing Voice AI startups in the world, you’ll love it here.Let’s build the future of voice automation together.We’re a top 50 AI app in a16z list: https://tinyurl.com/5853dt2xWe're also one of the top ranking startups on: https://leanaileaderboard.com/ABOUT THE ROLEThis is a hands-on, high-ownership role for ML engineers who want to build production models that actually ship, and perform under real-world constraints. As a Founding Senior Machine Learning Engineer at Retell, you’ll work across the ML stack to power human-like voice agents that handle millions of real-time phone conversations.You’ll fine-tune large language models and audio models, evaluate them with rigorous benchmarks (and human feedback), and deploy them into latency-sensitive, high-traffic systems. You’ll own model performance end-to-end—from training pipelines to post-deployment monitoring—and shape our ML strategy alongside the founding team.If you’re excited by hard technical challenges, fast iteration, and the opportunity to define how voice AI works at scale, this role is a rare chance to do it from the ground up.KEY RESPONSIBILITIESTrain & Tune Models – Fine-tune LLMs and audio models to maximize speed, accuracy, and production-readiness—pushing the frontier of real-time AI voice experiences.Benchmark & Evaluate – Build datasets, define rigorous metrics, and measure model performance across high-impact voice AI tasks to guide development.Deploy to Production – Work closely with engineering to ship models, monitor them in the wild, and ensure they stay fast, reliable, and accurate at scale.Run Human Evaluations – Build scalable pipelines to collect structured human feedback, benchmark subjective quality, and inform model iterations.Level Up Infrastructure – Design and maintain the ML infrastructure needed for fast experimentation, robust training, and continuous deployment. YOU MIGHT THRIVE IF YOUML Engineer with Real-World Experience – You’ve trained and shipped models in production. Bonus if you’ve worked with LLMs or audio models.Fluent in Modern ML Stack – You know your way around Python, PyTorch, and today’s ML tools—from training pipelines to evaluation benchmarks.Execution-Oriented – You move fast, take ownership, and focus on solving real problems over perfect ones.Startup-Ready – You’re adaptable, resilient, and energized by ambiguity and fast-changing priorities.Clear Communicator & Team Player – You collaborate well across functions and push decisions forward. JOB DETAILSJob Type: Full-time, 70 hr/week (50 hr/week onsite with flexible hours + 20 hr/week work from home)Cash: $200,000 - $280,000 base salary Equity: .0.15% – 0.35%Location: Redwood City, CA, USUS Visas: Retell AI is open to sponsoring work authorization for qualified candidates, including H1B/H-1B, TN, L-1, E-3, F-1 (OPT/CPT), and O-1 visas. OTHER BENEFITS100% coverage for medical, dental, and vision insurance$70/day DoorDash credit for unlimited breakfast, lunch, dinner, and snacks$200/month wellness reimbursement (gym, fitness classes, etc.)$300/month commuter reimbursement (gas, Caltrain, etc.)$75/month phone bill reimbursement$50/month internet reimbursement COMPENSATION PHILOSOPHYBest Offer Upfront: Choose from three cash-equity balance options, no negotiation needed.Top 1% Talent: Above-market pay (top 5 percentile) to attract high performers.High Ownership: Small teams, >$1M revenue/employee, and significant equity.Performance-Based: Offers tied to interview performance, not experience or past salaries. INTERVIEW PROCESSOnline Assessment (30 min): Coding questions on practical problem-solving (7 days to complete).Talent Screen (15min): chat with our recruiter to get a better sense of the role, the team, and what it’s like to work here.Technical Interview (45 min): Machine Learning specific coding Interview.Technical Interview (45 min): Live Practical Systems Design and Coding Interview.Onsite/Virtual Interviews (3 hrs): Hosted in our office if located in the Bay Area or virtual, with three rounds:ML System Design: A non-coding interview focused on whiteboarding and high-level system architecture.ML Question Deep Dive: In-depth discussion exploring your approach to a machine learning problem.Backend + AI Practical: A hands-on coding interview combining backend development with AI integration.Offer: Final stage, pending decision and offer discussion.

false

About UsTavus is a research lab pioneering human computing. We’re building AI Humans: a new interface that closes the gap between people and machines, free from the friction of today’s systems. Our real-time human simulation models let machines see, hear, respond, and even look real—enabling meaningful, face-to-face conversations. AI Humans combine the emotional intelligence of humans with the reach and reliability of machines, making them capable, trusted agents available 24/7, in every language, on our terms.Imagine a therapist anyone can afford. A personal trainer that adapts to your schedule. A fleet of medical assistants that can give every patient the attention they need. With Tavus, individuals, enterprises, and developers can all build AI Humans to connect, understand, and act with empathy at scale.We’re a Series A company backed by world-class investors including Sequoia Capital, Y Combinator, and Scale Venture Partners.Be part of shaping a future where humans and machines truly understand each other.The Role We’re looking for an AI Researcher to join our core AI team and push forward the science of audio-visual avatar generation. If you thrive in high-speed startup environments, enjoy experimenting with generative models, and love seeing your research ship into production then you’ll feel right at home.Your Mission 🚀Research and develop audio-visual generation models for conversational agents (e.g. Neural Avatars, Talking-Heads).Focus on models that are tightly coupled with conversation flow, ensuring verbal and non-verbal signals work seamlessly together.Experiment with diffusion models (DDPMs, LDMs, etc.), long-video generation, and audio generation.Collaborate with the Applied ML team to bring your research into real-world production.Stay ahead of the latest advancements in multimodal generation — and help shape the next wave.You’ll Be Great At This If You Have:A PhD (or near completion) in a relevant field, or equivalent hands-on research experience.Experience applying image/video generation models in practice.Strong foundations in generative modeling and rapid prototyping.Deep familiarity with diffusion models, including recent advances in efficiency.Good understanding of video-language models and multimodal generation.Proficiency in PyTorch and GPU-based inference.Nice-to-HavesExperience with long-video or audio generation.Skills in 3D graphics, Gaussian splatting, or large-scale training setups.Broader exposure to generative models and rendering.Familiarity with software engineering best practices.Publications in top-tier or respected venues (CVPR, NeurIPS, BMVC, ICASSP, etc.).Location Preferred: San Francisco (hybrid) or London (office opening soon). Remote within U.S. or Europe available for exceptional candidates.

true

Hi, we're The Browser Company 👋 and we're building a better way to use the internet. Browsers are unique in that they are one of the only pieces of software that you share with your parents as well as your kids. Which makes sense, they're our doorway to the most important things — through them we socialize with loved ones, work on our passion projects, and explore our curiosities. But on their own, they don’t actually do a whole lot, they’re kind of just there. They don’t help us organize our messy lives or make it easier to compose our ideas. We believe that the browser could do so much more — it can empower and support the amazing things we do on the internet. That’s why we’re building one: a browser that can help us grow, create, and stay curious. To accomplish this lofty task, we’re building a diverse team of people from different backgrounds and experiences. This isn’t optional, it’s crucial to our mission, as we need a wide range of perspectives to challenge our assumptions and shape our browser through a bold, creative lens. With that in mind, we especially encourage women, people of color, and others from historically marginalized groups to apply.About The RoleAs our founding ML Engineering Manager at the Browser Company, you’ll build our strategy and define how we incorporate ML to advance Dia’s product vision. The browser holds most of the context about your workday, from memory of the tasks you’re trying to accomplish to access to all of your web apps. We use ML and AI to turn that context into high‑utility experiences that feel personal and improve over time, grounded in capabilities like computer‑use, memory, and web‑app integrations.Dia’s Assistant doesn’t just execute actions, it also suggests and recommend tasks, and learns which choices drive real outcomes. We leverage modern training techniques such as SFT, RL, and GEPA to optimize these experiences while protecting privacy. To move fast and learn continuously, we’re building a first‑class ML developer environment: curated data pipelines, tight experiment loops, offline/online evals with telemetry, and one‑click deploys with strong observability.Our Management PhilosophyEngineering Managers at Browser Company are hands-on technical leaders who build high-performing and psychologically-safe teams with a diverse group of individuals. You’ll work closely with your team to make product decisions, prioritize work, ship features, and promote an engineering culture of knowledge sharing and mentorship. Engineering Managers follow the same onboarding pathway as an IC engineer to learn our product data, and build processes, then ramp into leadership. Overall you will...Define and build our ML strategy, sequencing bets that improve Dia’s assistant and measurable user outcomes. You’ll stay ahead of the latest AI advancements and translate them into strategic opportunities for Dia’s roadmap.Prototype, architect, and ship LLM‑powered features; establish techniques to train models that improve over time and personalize experiences, partnering with Design and Product Engineering to balance quality, speed, and scale for real‑world use.Audit and evolve the ML stack and infrastructure - spanning Swift for on-device inference and Python for models and tooling - to support both encoder and decoder model families across client and server. Over time, scale the system using fine-tuned open-source LLMs.Partner on privacy and security by working with Security and Infra on data stewardship, deployment strategies, and responsible scaling. Establish ML Developer Experience by building tooling and workflows for high quality data curation, experimentation (fine-tuning, RL, prompting), evals, and continuous training to improve the models that power Dia.Support and build a talented team of machine learning engineers, helping them grow both technically and with a product mindset through fast iteration cycles. You’ll play a key role in contributing across the engineering org as we scale—owning processes, recruiting, and onboarding—and proactively improve architecture and practices to enhance performance, stability, and maintainability.Technical Projects You’ll Shape With Us…Browser context engine: learn a unified embedding space that fuses app integrations, enterprise connectors, and on-device signals to enable low-latency retrieval, routing, and personalizationPersonalize the command bar: develop ranking, intent understanding, and context-aware suggestions; fine-tune and evaluate models to measurably boost relevance and engagementEvolve our data flywheel by defining how we instrument product signals, design collection/storage pipelines, create labeling/evaluation loops, and continuously retrain to improve feature quality and personalization Qualifications6+ years of experience training, optimizing, and productionizing modern ML models, especially ones that run in a real-world product environment (bonus if you’ve worked closely with transformer models)3+ years mentoring and leading senior engineers with a track record of tech-leading critical work and setting a sustainable execution pace. You're able to execute on critical projects, own large, complex codebases and drive initiatives within your team.You love to keep up with the latest advancements in AI and are excited to apply the latest models and techniques to push the boundaries of what's possible in a browserYou have production experience with Python and have experience fine-tuning open-source LLMs and going beyond simple LoRA fine-tuningYou’re pragmatic, motivated by nebulous problems, and excited to work in a startup environment with quick product validation cycles.We’re primarily focused on hiring in North American time zones and require that folks have 4+ hours of overlap time with team members in Eastern Time Zone.Compensation and BenefitsOur total compensation package for full-time employees includes base salary, equity, and benefits. The annual salary range for this role is $300,000- $360,000 USD. The actual salary offered will vary based on experience level and interview performance.Benefits: We also offer a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. To learn more, visit go.atlassian.com/perksandbenefits.Location: We’re a remote-friendly company and can hire in any country where Atlassian has a legal entity. If you live in New York (or want to visit), you’re welcome to work from our beautiful office in Williamsburg.The Browser Company is a well-funded, ambitious startup of close to 100 people (and growing!) who are passionate about building great products. We are a remote-first, distributed team, with the option to work from office in Brooklyn, New York. We strongly support diversity and encourage people from all backgrounds to apply.  🚙 To read more about what we value as a company, check out Notes on Roadtrips on our blog.

false

At Black Forest Labs, we’re on a mission to advance the state of the art in generative deep learning for media, building powerful, creative, and open models that push what’s possible.  Born from foundational research, we continuously create advanced infrastructure to transform ideas into images and videos.Our team pioneered Latent Diffusion, Stable Diffusion, and FLUX.1 – milestones in the evolution of generative AI. Today, these foundations power millions of creations worldwide, from individual artists to enterprise applications. We are looking for a 3D Researcher to bring precise camera control to our image and video generation models. Role and Responsibilities Training large-scale Diffusion (transformer) models for camera-controllable image and video generation Developing conditioning mechanisms for 3D camera parameters (poses, trajectories, intrinsics) in diffusion models Rigorously ablating design choices for 3D control and communicating results & decisions with the broader team Reasoning about the speed and quality trade-offs of 3D-aware architectures What we look for Experience training large-scale Diffusion models for image and video data Strong understanding of 3D projective geometry, camera models, and coordinate systems Experience with 3D-aware generative models or neural rendering techniques (NeRFs, 3DGS, etc.) Integrating geometric priors and 3D conditioning into neural networks Strong proficiency in PyTorch, transformer models and other NN architectures Deep understanding of training techniques such as FSDP, low precision training, and model parallelism Nice to have: Experience with multi-view consistency in generative models Understanding of camera calibration, structure-from-motion, or SLAM  

false

About GPTZeroGPTZero is on a mission to restore trust and transparency on the internet. As the leading AI detection platform, we empower educators, students, journalists, marketers, and writers to navigate the evolving landscape of AI-generated content. With millions of users and institutions relying on us, we’re building a category-defining company at the intersection of AI and information integrity. Our team comes from high-performing engineering cultures, including Uber, Meta, Perplexity, Amazon, Affirm, and leading AI research labs, including Princeton, Caltech, MILA, and Vector.About this role:In this role, you'll build the next generation of AI tools that promote critical thinking, assist in the writing process, and verify document factuality. The ideal candidate is someone who is adept at creating reliable AI agents, prompt engineering, possesses a great product sense, and is also an excellent software engineer. You'll be working on a fast-paced team of passionate builders to create industry-defining software that has attracted millions of users globally.What you'll contribute:Fine-tune and evaluate state-of-the-art language modelsOptimize prompts to maximize classification accuracy, personalize outputs, and enforce style guidelinesDevelop multi-agent workflows incorporating data from diverse sources using RAGImprove and iterate on AI agents using observability and experimentation toolsStay up-to-date with the latest literature and emerging technologies to solve novel problemsWork closely with product and design teams to develop intuitive applications that create societal impactQualifications4+ YOE in Python1+ YOE in LLM framework like Langchain or LlamaIndex1+ YOE with agentic or RAG applicationsStrong exploratory data analysis (EDA) skills to effectively leverage data in a way that informs pragmatic solutionsExperience pushing the cutting-edge in LLM abilities on novel tasks with subjective outputsExcellent software engineer with experience building highly extensible and modular codebases, as well as complex pipelinesSelf-starter (pitch, plan, and implement as a project owner in a fast-paced team)Highly motivated to make positive societal impactAbility to wear multiple hats and be a leader as our team growsVisa for work in Canada or USBonus:Strong open-source portfolioPublications at top-tier ML venuesExperience working in an early-stage startup environmentExperience with a prompt optimization framework like DsPY or TextGrad

false

About BasisBasis equips accountants with a team of AI agents to take on real workflows.We have hit product-market fit, have more demand than we can meet, and just raised $34m to scale at a speed that meets this moment.Built in New York City. Read more about Basis here.About the TeamWe build the agentic ML systems that power Basis’s AI Accountant—so it can read documents, reason over context, and complete real accounting workflows safely and accurately.We’re practitioners of the new AI paradigm: rather than just tuning a model, we optimize the system around it—tools, memory, retrieval, orchestration, and evaluation. We push model providers to their limits when necessary (custom runtimes, bigger containers, nonstandard packages) and run the experiments required to learn quickly.We work from first principles with tight loops alongside Research, Product, Platform, and Accounting SMEs. We think in systems and care deeply about observability, clear abstractions, and code that’s easy to reason about in production.About the RoleAs an Engineering Leader on the ML Systems team, you’ll be responsible for achieving company-level outcomes through the people and systems you build. Your job is to make the team successful—to deliver ambitious technical goals while fostering an environment where exceptional engineers can do their best work.You’ll operate across research and production, experiment and impact—bridging strategy and execution. You’ll make hard trade-offs explicit, design frameworks for fast iteration, and ensure that the entire team learns faster than the problems evolve.This is a hands-on leadership role: you’ll drive technical direction, architect systems, and review critical code—but your real leverage will come from clarity, conviction, and how effectively you grow others.What you’ll be doing:1. Build and lead the applied-ML organizationHire and grow a world-class team of ML and systems engineers; set crisp goals and coach continuous development.Foster a culture of rigor, iteration, and shared learning—where people move fast and stay grounded in reality.Establish clear processes for experimentation, evaluation, and delivery; make success criteria objective and comparable.Be a source of clarity and calm when things are ambiguous or hard.2. Drive ML systems strategy and executionDefine and evolve our multi-agent architecture: autonomy boundaries, orchestration logic, context management, and safety layers.Own evaluation infrastructure—offline, online, and hybrid—that lets us ship models with confidence and traceability.Integrate retrieval, memory, and context management into production-grade agent loops; ensure stability under real workloads.Align closely with Research, Product, and Platform to translate insights into production systems with measurable impact.3. Elevate the craftInsist on clean abstractions, legible systems, and deep observability; make complexity visible and manageable.Set and uphold high standards for experimentation, documentation, and decision quality.Continuously improve team processes—reviews, onboarding, retros, performance cycles—to compound speed and quality.Coach engineers not just to build better models, but to think better about systems. 📍 Location: NYC, Flatiron office. In-person team.What We’d Love to SeeThink in systems—models, people, organizations—and can operate across all three.Care about clarity and iteration more than flash; you ship, learn, and refine relentlessly.Have conviction in your decisions but stay open to being wrong.Are driven by both technical excellence and the growth of those around you.See ambiguity as an invitation to lead.What Success looks like in this roleProcess-oriented: Skilled at breaking down complex problems into clear, repeatable steps and managing execution.Strong communicator: Clear in explaining concepts and comfortable collaborating across all levels of seniority.First-principles reasoner: Question assumptions and apply lessons creatively to new situations.Company-builder: Eager to lay groundwork both technically and culturally as we rapidly scale.Office lover: Prefers face-to-face interactions in our NYC office.All-in: Driven to seize a massive opportunity, accelerate growth, and commit deeply to Basis’s success. In accordance with New York State regulations, the salary range for this position is $100,000 –$300,000. This range represents our broad compensation philosophy and covers various responsibility and experience levels. Additionally, all employees are eligible to participate in our equity plan and benefits program. We are committed to meritocratic and competitive compensation.

false

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 mistral.ai/careers. About The Job: Technical Lead, Applied AI Mistral AI is seeking a Technical Lead, Applied AI to drive the technical strategy, execution, and delivery of complex AI solutions for our enterprise customers. In this role, you will lead a project teams of Applied AI Engineers, ensuring the successful deployment of Mistral AI products and the development of high-impact, scalable AI use cases. You will act as the primary technical point of contact for our most strategic customers, guiding them through the entire lifecycle—from pre-sales to post-implementation—while collaborating closely with research, product, and engineering teams to shape the future of our offerings. As a Technical Lead, you will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral’s technological vision. What you will do - Deliver as an IC the critical lines of codes of our complex projects, you’ll be hands-on and de-risk the critical parts of our complex projects. You’ll stay deeply involved in coding, reviewing, and optimizing AI solutions.- Lead technical teams of Applied AI Engineers, providing mentorship, technical guidance, and best practices for deploying state-of-the-art GenAI applications across industries.- Lead technical discussions during pre-sales, translating customer requirements into actionable solutions and communicating Mistral’s technological advantages to diverse stakeholders.- Design and oversee the implementation of complex AI systems, including fine-tuning, RAG, agentic workflows, and custom LLM applications, ensuring alignment with Mistral’s product roadmap and open-source initiatives.- Drive innovation by identifying emerging trends in AI, evaluating new tools and methodologies, and championing best practices for fine-tuning, inference, and deployment.- Work closely with product managers, researchers, and engineers to ensure seamless integration of customer feedback into Mistral’s product development cycle. About you- You are fluent in English.- You hold a PhD or Master’s degree in AI, Machine Learning, Computer Science, or a related field.- You have 7/8+ years of experience in AI/ML, with at least 2+ years in a technical leadership role (e.g., Tech Lead, Engineering Manager, or Solutions Architect) focused on AI products or enterprise solutions.- You have a proven track record of leading teams to deliver complex AI projects, from prototyping to production, in industries such as tech, finance, healthcare, or industrial automation.- You possess deep expertise in fine-tuning LLMs, advanced RAG, agentic systems, and deploying NLP applications at scale.- You are proficient in Python, PyTorch, and modern AI frameworks (e.g., LangChain, Hugging Face). Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools is a plus.- You have strong software engineering skills, including API design, backend/full-stack development, and system architecture.- You excel in technical communication, with the ability to articulate complex concepts to both technical and non-technical audiences, including executives and engineers.- You thrive in fast-paced, collaborative environments and are passionate about mentoring and growing technical talent. Ideally, you have:- Contributed to open-source projects, particularly in the LLM or AI space.- Experience in customer-facing roles (e.g., Solutions Architect, Customer Engineer, or Technical Product Manager) with a focus on enterprise AI adoption.- A track record of driving technical strategy and influencing product direction based on customer needs and market opportunities. Why join us? You’ll have the opportunity to shape the future of AI adoption in enterprises, work with a world-class team, and contribute to open-source projects that impact millions. If you’re excited about leading technical innovation and solving real-world challenges with AI, we’d love to hear from you!