JAX Jobs

Anthropic

The Safeguards ML Inference Path team designs, builds, and operates the production infrastructure that powers Claude's ML based safety systems. We collaborate closely with safety researchers and inference engineers to bring new classifiers and novel classes of ML defenses to production. We own the research → production transfer of new safety technologies that is on the critical path for every Claude model launch. We build for scale, serving thousands of ML classifiers for all requests on the token generation path and for every platform Claude runs on. We are looking for engineers who have deep expertise in productionizing ML systems, working at the intersection of machine learning, large-scale distributed systems, and AI safety, developing the platforms and tools that enable our safeguards to operate reliably at scale.

Fireworks is seeking a Member of Technical Staff on the Research team, designed for PhD candidates who want their work to reach production. This role involves pushing the boundaries of generative AI, advancing LLMs and multimodal systems through foundational research. You will enhance model efficiency, accuracy, and scalability, directly shaping high-performance AI infrastructure. You will be paired with a senior researcher as a mentor and given a real research problem from day one, collaborating with top experts in deep learning, distributed systems, and optimization. The work you contribute will be deployed by leading companies, often within weeks.

SpaceXAI is seeking a multimodal engineer for the Imagine Model Team to develop cutting-edge AI experiences beyond text, focusing on high-fidelity understanding and generation across image and video modalities, with audio integration where it enhances visual content. Responsibilities cover data curation, modeling, training, inference serving, and product integration across pretraining and post-training phases. The role involves close collaboration with product teams to advance model frontiers and deliver exceptional end-to-end user experiences.

$180k - $440k

SpaceXAI is seeking a Member of Technical Staff to join their multimodal team and advance the understanding and generation of AI across image, video, audio, and text. This role involves working across the full stack, from data curation and pre-training to alignment, infrastructure, and end-to-end product experiences. You will collaborate with various teams to deliver cutting-edge multimodal reasoning, world modeling, tool use, agentic behaviors, and human-AI collaboration capabilities. The goal is to build models that can perceive, reason about, and interact with the world in real-time at an unprecedented level.

$180k - $440k

SpaceXAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. The RL infrastructure team is looking for an engineer to help with low precision RL training and inference. This role involves designing and optimizing the inference stack for all shapes of RL workloads, analyzing and addressing performance bottlenecks in large-scale RL systems, and working closely with the modeling team to efficiently implement novel RL techniques and algorithms.

$180k - $440k

SpaceXAI is seeking an engineer to join the RL infrastructure team to help develop our RL training framework. The team is small, highly motivated, and focused on engineering excellence, operating with a flat organizational structure where all employees are expected to be hands-on and contribute directly to the company's mission. This role requires strong initiative, curiosity, work ethic, prioritization, and communication skills.

$180k - $440k

SpaceXAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. The Grok Voice Model team is building the world's best voice AI, delivering smooth, natural, low-latency spoken interactions that are expressive, multilingual, and reliable across devices and real-time scenarios. The team owns the full training pipeline, from massive data curation and premium audio processing to frontier speech-language pre-training and intensive post-training to push quality, speed, and stability to the limit. The goal is to make talking to AI feel like conversing with a charming, kind, and knowledgeable person, and exceptionally smart, execution-oriented engineers are sought to achieve this.

$150k - $450k

You will help define how machine learning models run across Cloudflare’s global network, from frontier open LLMs and real-time voice models to customer-deployed models served on heterogeneous GPUs and next-generation accelerators. You’ll work with systems engineers, product teams, hardware partners, and AI/ML engineers to bring models into production with low latency, strong reliability, and efficient resource use. This role combines applied ML, inference optimization, evaluation, and production engineering, with a focus on benchmarking models, improving serving performance, validating quality, and building tooling that helps Cloudflare and its customers ship AI applications at Internet scale.

Cohere

Cohere is seeking a Staff Software Engineer to join our internal infrastructure team, responsible for building and operating world-class infrastructure and tools for training, evaluating, and serving Cohere's foundational AI models. You will work closely with AI researchers to support their AI workload needs on cutting-edge systems, focusing on stability, scalability, and observability. This role involves building and operating superclusters across multiple clouds, directly accelerating the development of industry-leading AI models. Participation in a 24x7 on-call rotation is required and compensated.

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'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.

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

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

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.

Baseten is seeking a Forward Deployed Engineer (Training) to work directly with leading AI companies, taking ownership of their technical outcomes on the Baseten platform. This role involves tackling complex challenges in serving and improving AI models at scale, spanning the entire model lifecycle from inference to post-training and the systems that connect them. You will act as a technical advisor, guiding customers from initial problem framing through to production deployment, and ensuring the quality and performance of their AI workloads through rigorous evaluation and optimization.

Cohere

Cohere is seeking a senior engineer to join our team, focusing on the practical challenges of deploying AI systems at scale in production environments. This hands-on, engineering-driven role involves working with frontier AI models, building scalable solutions, and bridging research concepts with real-world implementations. You will contribute to both engineering and research efforts, designing and writing high-performing software for model training, developing new tools to support LLM research, and collaborating with various engineering and scientific teams. We provide access to world-class compute resources, data, and talent to enable you to do your best work.