PyTorch Jobs

Anthropic

As a Research Engineer within Reinforcement Learning, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to the research direction. You'll work on fundamental research in reinforcement learning, creating 'agentic' models via tool use for open-ended tasks such as computer use and autonomous software generation, improving reasoning abilities in areas such as mathematics, and developing prototypes for internal use, productivity, and evaluation.

Anthropic

Anthropic is seeking a Research Engineer to join its Pretraining team, focusing on developing the next generation of large language models. This role operates at the intersection of cutting-edge research and practical engineering, aiming to build safe, steerable, and trustworthy AI systems. The mission is to ensure that transformative AI systems are aligned with human interests and are beneficial for society. The team is dedicated to pushing the boundaries of AI while prioritizing safety and ethics.

Anthropic

Anthropic's ML Performance and Scaling team is responsible for training our production pretrained models, a critical function that directly shapes the company's future and its mission to build safe, beneficial AI systems. As a Research Engineer on this team, you will ensure our frontier models train reliably, efficiently, and at scale. This demanding, high-impact role requires deep technical expertise and a passion for large-scale ML systems, operating at the boundary between research and engineering. You will work across the entire production training stack, including performance optimization, hardware debugging, experimental design, and launch coordination, responding to critical production issues during launches.

Fireworks is seeking a Developer Advocate to be the voice of their specialized intelligence platform for developers. In this role, you will be responsible for making Fireworks the go-to platform for building, fine-tuning, and serving frontier open models in production. This position requires a dual focus: you must be a hands-on engineer who ships code and understands technical nuances, and a public technical communicator who can clearly articulate complex topics through writing, speaking, and community engagement. You will be at the forefront of a rapidly evolving field, consistently staying ahead of new model releases and making it look repeatable rather than heroic. As one of the first advocates on the team, you will help set the standards for content, launch responses, and team presence.

Perplexity is seeking top-tier AI Research Scientists and Engineers to advance our AI products and capabilities, focusing on building the future of AI-powered search and agent experiences. You will contribute to SOTA experiences that handle hundreds of millions of queries and continue to scale rapidly. Depending on your interests and expertise, you can join one of three specialized teams: the Core Research Team focusing on foundational models, the Agent Products Team fine-tuning models for agent and product experiences, or the Comet Agent Team dedicated to developing and enhancing the Comet Agent product.

Runpod is seeking a Forward Deployed Engineer to join their Revenue Team and support the growth of their AI Developer Cloud platform. This role focuses on providing technical insights, resolving customer challenges, and building trust to ensure a seamless and delightful Runpod experience. You will work closely with customers, sales, product, engineering, and support teams to enhance customer satisfaction and drive product improvements. The ideal candidate combines technical expertise with strong communication skills to address technical challenges, guide onboarding, and collaborate across functions.

$100k - $180k

Applied Intuition is seeking a Perception & Fusion Engineer to join their team in developing, integrating, and maintaining real-time sensor software solutions for autonomous vehicles across various domains. You will design, develop, and integrate sensor fusion algorithms to interface with different platforms and support autonomy team objectives. This role involves developing autonomous sensor controllers to fuse information from state-of-the-art sensor systems like EO, IR, acoustics, radar, and RF.

$10k - $20k

World Labs is a frontier AI research and product company focused on spatial intelligence, advancing beyond large language models. Co-founded by leading researchers, the company is pioneering world models that perceive, generate, reason, and interact with virtual and physical worlds. Their flagship product, Marble, transforms various media into navigable 3D worlds, with applications in gaming, film, architecture, robotics, and immersive experiences. Backed by significant investment, World Labs is building a world-class team at the intersection of AI research and real-world deployment.

$250k - $325k

World Labs is a frontier AI research and product company focused on spatial intelligence, co-founded by Dr. Fei-Fei Li, Justin Johnson, and Ben Mildenhall. The company is developing world models that can perceive, generate, reason, and interact with virtual and physical worlds, with its flagship product Marble transforming text, images, and video into navigable 3D worlds. Backed by leading investors, World Labs is building a world-class team at the intersection of AI research and real-world deployment.

$250k - $350k

World Labs is a frontier AI research and product company focused on spatial intelligence, developing world models that perceive, generate, reason, and interact with virtual and physical worlds. Their flagship product, Marble, transforms various inputs into navigable 3D worlds for applications in gaming, film, architecture, robotics, and immersive digital experiences. Backed by significant investment, World Labs is building a world-class team at the intersection of AI research and real-world deployment. This role involves building a production-grade web application for 3D Gaussian Splat scene generation, editing, and publishing. It's a high-ownership, full-stack role with a backend focus, bridging R&D and frontend. You will work across graphics/ML algorithms, backend services, and frontend UI, transforming proof-of-concepts into reliable, debuggable, and delightful shipped features. The ideal candidate thrives on making complex systems work smoothly in production and continuously improving them based on user feedback.

$200k - $325k

World Labs is a frontier AI research and product company advancing spatial intelligence. We are seeking a Performance Engineer to optimize our large generative world models for both training and serving, ensuring they run as fast as the hardware allows. This hands-on, individual-contributor role involves identifying and eliminating performance bottlenecks across the entire stack, from low-level kernel optimization to fleet-wide serving efficiency. You will work closely with researchers to accelerate their models and productionize them for efficient deployment.

$200k - $300k

Synthesia is seeking an Applied Research Engineer to join their Video team and contribute to building the next generation of production-grade foundation models for human-centric video generation. This role involves working at the intersection of large-scale generative modeling, distributed systems, and production engineering, with a focus on developing and optimizing video base models for realistic, controllable, and expressive synthetic humans. This is an applied research position with direct product impact, requiring the candidate to advance training recipes, scale distributed systems, improve evaluation frameworks, and optimize inference for real-world deployment. The work will directly influence models used by tens of thousands of businesses globally.

Anthropic

We are seeking a Research Engineer for our Code RL team, focused on advancing AI models' capabilities in writing, editing, testing, debugging, and shipping real software. This role involves designing RL environments, coding tasks, and reward signals, as well as running training experiments on frontier models. You will diagnose model performance, improve pipeline speed and reliability, and contribute to areas like agentic coding behaviors, code correctness, and autonomous engineering. The position blends cutting-edge research with practical engineering to build high-quality, scalable AI systems.

Anthropic

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the RL Teams Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.6 and Opus 4.6. Our work spans several key areas: - Developing systems that enable models to use computers effectively - Advancing code generation through reinforcement learning - Pioneering fundamental RL research for large language models - Building scalable RL infrastructure and training methodologies - Enhancing model reasoning capabilities We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish. About the Role We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to safely write correct, fast code for accelerators. You'll need to know accelerator performance well to turn it into tasks and signals models can learn from. Specifically, you will: - Invent, design and implement RL environments and evaluations. - Conduct experiments and shape our research roadmap. - Deliver your work into training runs. - Collaborate with other researchers, engineers, and performance engineering specialists across and outside Anthropic. You may be a good fit if you: - Have expertise with accelerators (CUDA, ROCm, Triton, Pallas), ML framework programming (JAX or PyTorch). - Have worked across the stack – kernels, model code, distributed systems. - Know how to balance research exploration with engineering implementation. - Are passionate about AI's potential and committed to developing safe and beneficial systems. Strong candidates may also have: - Experience with reinforcement learning. - Experience porting ML workloads between different types of accelerators. - Familiarity with LLM training methodologies. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $350,000—$850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Anthropic

The Interpretability team at Anthropic is dedicated to understanding how large language models work, believing that a mechanistic understanding is key to making advanced AI systems safe and reliable. This role involves building and maintaining the specialized infrastructure for interpretability research, akin to performing 'neuroscience' on neural networks. The work spans the entire lifecycle of a production language model, from pretraining and inference to performance optimization, pushing the boundaries of hardware and software to address critical bottlenecks. As interpretability research matures and is applied to safety audits on frontier models, engineering and infrastructure have become crucial, making this role directly impactful on one of AI's most significant open problems.

Anthropic

Anthropic's ML Performance and Scaling team is responsible for training the company's production pretrained models, a critical function that directly shapes the future of Anthropic and its mission to build safe, beneficial AI systems. As a Research Engineer on this team, you will ensure that frontier models train reliably, efficiently, and at scale. This role bridges the gap between research and engineering, involving work across the entire production training stack, including performance optimization, hardware debugging, experimental design, and launch coordination. During model launches, the team operates in close collaboration, addressing production issues that require immediate attention.

Anthropic

As a Research Engineer on our team, you will work end-to-end across the entire model stack, identifying and addressing key infrastructure blockers on the path to scientific AGI. You should have familiarity with elements of language model training, evaluation, and inference, and be eager to quickly dive into and get up to speed in areas where you are not yet an expert. This may include performance optimization, distributed systems, VM/sandboxing/container deployment, and large-scale data pipelines. Join us in our mission to develop advanced AI systems that push the frontiers of science and benefit humanity.

Anthropic

Pioneering the next generation of AI requires breakthrough innovations in GPU performance and systems engineering. As a GPU Performance Engineer, you'll architect and implement the foundational systems that power Claude and push the frontiers of what's possible with large language models. You'll be responsible for maximizing GPU utilization and performance at unprecedented scale, developing cutting-edge optimizations that directly enable new model capabilities and dramatically improve inference efficiency. Working at the intersection of hardware and software, you'll implement state-of-the-art techniques from custom kernel development to distributed system architectures. Your work will span the entire stack—from low-level tensor core optimizations to orchestrating thousands of GPUs in perfect synchronization. Strong candidates will have a track record of delivering transformative GPU performance improvements in production ML systems and will be excited to shape the future of AI infrastructure alongside world-class researchers and engineers.

Anthropic

Anthropic is seeking a Research Engineer to join its Pre-training team, focusing on developing the next generation of large language models. This role operates at the intersection of cutting-edge research and practical engineering, contributing to the creation of safe, steerable, and trustworthy AI systems. The team is dedicated to ensuring that transformative AI systems are aligned with human interests and societal benefit.

Anthropic

As a Research Engineer within Reinforcement Learning, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to the research direction. You'll work on fundamental research in reinforcement learning, creating 'agentic' models via tool use for open-ended tasks such as computer use and autonomous software generation, improving reasoning abilities in areas such as mathematics, and developing prototypes for internal use, productivity, and evaluation.