Reinforcement Learning Jobs

SpaceX is building Super Intelligence to help humanity understand the universe, developing the full Super Intelligence stack from supercomputers to large language models and applications. This role focuses on the most critical post-training and reinforcement learning challenges, including reward modeling, preference optimization (RLHF/DPO), and RL for improving reasoning, truthfulness, and real-world capabilities. You will work on cutting-edge AI problems with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.

$180k - $600k

Glean is seeking Machine Learning Engineers to join the Enterprise Brain team, focusing on building proactive AI products that revolutionize enterprise workflows by automating tasks and enhancing user productivity. This role involves leveraging deep user understanding and state-of-the-art enterprise graphs, utilizing LLMs, advanced ML techniques, agent orchestration, and cutting-edge ranking methods. You will contribute to a secure, open platform that redefines how enterprises find, use, and act on knowledge, with a focus on enterprise trust and scalability.

$200k - $280k

Figure is an AI robotics company developing autonomous general-purpose humanoid robots with the goal of shipping robots with human-level intelligence. These robots are engineered to perform a variety of tasks in both home and commercial markets. We are seeking a Reinforcement Learning Engineer to focus on the development, training, deployment, and evaluation of advanced reinforcement learning algorithms specifically for the whole-body control of our humanoid robots.

$150k - $350k

OpenAI

The Human Flourishing team is dedicated to ensuring AI systems understand and advance human flourishing, aligning AI capabilities with human values and long-term goals. This role involves measuring and improving models' understanding of human values, supporting user agency, and helping users achieve their long-term objectives. The team also focuses on scaling tangible impact in domains like education and mental health, working across research, product, and partnerships to benefit a large user base. Recent work includes Beneficial RL and the MentalHealthBench benchmark.

$380k - $500k

Anthropic

Anthropic is seeking individuals for a paid, fixed-term research residency program, lasting between six weeks and six months. This program is designed for experienced professionals, such as professors in quantitative disciplines, technical founders, or staff-level engineers, who are looking to transition into full-time work focused on ensuring AI systems are safe and beneficial for humanity. While a background in machine learning is not strictly required, candidates should be motivated by AI safety and excited about empirical AI research. The residency offers a scoped project with direct mentorship from Anthropic researchers, access to Claude models and GPU compute, and connections to the AI safety and security research community.

$350k - $500k

Turing's Enterprise AI unit operates with the speed and focus of a startup, building advanced AI solutions for leading enterprises. As a Forward-Deployed AI Engineer, you will be at the forefront of applied AI in the workplace, shaping how AI is integrated into critical business workflows. You will own outcomes end-to-end, from identifying high-value customer problems and shaping architecture to building production systems and collaborating directly with senior client leaders. This role involves developing generative AI solutions that drive measurable impact and ROI within large institutions, offering an intellectually challenging environment for those seeking difficult, high-impact work.

$200k - $250k

The CRAFT (Capabilities, Routing, Adaptation & Fine-Tuning) team at CoreWeave is focused on developing tools that enable AI agents to learn from experience, a crucial step towards autonomous long-task execution. The team has already released innovative projects like ART for RL, RULER for reward functions, and Serverless RL for infrastructure management. They are now tackling remaining challenges in agent training, such as reducing human labor in environment creation and improving data efficiency. This role offers a significant opportunity to contribute to hard-tech advancements in a rapidly growing market, with the potential to shape the future of self-improving AI agents.

$182k - $242k

CoreWeave is seeking an early member for its Applied Training team to build the research infrastructure that enables AI pioneers to train models with confidence. This role addresses the problem of AI labs spending valuable research time on cluster setup and operations instead of innovation. You will contribute to the roadmap and develop solutions for our Kubernetes-native research cluster platform or sandbox client for agentic training and evaluation, aiming to provide frontier lab-level infrastructure to all CoreWeave customers.

$182k - $242k

As an AI engineer on the CRAFT team, you will bring research into production and build products across our roadmap, including tools for agent evaluation and continuous improvement. You’ll own features from the user experience through backend services and model integrations. You’ll turn research in post-training and model evaluation into products that help customers understand and improve their models. We’re looking for strong product instincts to translate research methods into intuitive workflows and delightful user experiences. You’ll work closely with researchers and customers to define problems, make practical tradeoffs, and deliver products in an evolving space. CRAFT is a small team with significant autonomy over our roadmap and priorities.

$182k - $242k

Turing's mission is to accelerate superintelligence to drive real economic progress. The company works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks. Turing also partners with Fortune 500 enterprises to build and deploy end-to-end agentic AI systems within mission-critical workflows. This role involves leading the Turing Enterprise AI Platform technical team, which is being built out for a late 2025 SDK release and a Q1 2027 tenant onboarding. The goal is to grow the team to eight to ten members and collaborate with the Chief AI Architect on client-facing architecture and evaluation.

As a multimodal engineer on the Imagine Model Team, you will develop cutting-edge AI experiences beyond text, with a strong focus on enabling high-fidelity understanding and generation across image and video modalities, while also incorporating audio where it enhances visual content. Responsibilities span data curation, modeling, training, inference serving, and product integration, covering both pretraining and post-training phases. You will collaborate closely with product teams to push model frontiers and deliver exceptional end-to-end user experiences.

$180k - $440k

You'll join the Grok Voice Model team as a software engineer. You'll design, build, and run the software systems behind Grok Voice, which delivers natural, low-latency, multilingual spoken interactions across devices and in real time. The team owns the full engineering stack behind the model, from large-scale data processing to distributed training to production deployment.

$150k - $450k

NVIDIA Research is seeking PhD-level students for a research internship focused on groundbreaking work at the intersection of AI, GPU computing, Formal Methods, and Electronic Design Automation (EDA). This role offers the chance to influence the future of chip design, which is being transformed by AI and GPU acceleration. Interns will gain broad exposure to EDA algorithms, agentic AI, LLMs, and GPU computing, with specific research interests including GPU-accelerated optimization, physical design, formal methods, agentic AI, and reinforcement learning techniques.

$0k - $0k

NVIDIA is seeking a motivated Deep Learning engineer to integrate advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, and SGLang. You will work with the team that created communication libraries like NCCL and NVSHMEM, and technology like GPUDirect, to scale Deep Learning and HPC applications. Your work will directly impact AI application performance by improving communication between GPUs, making AI toolkits easier for the community to use. This role offers an outstanding opportunity for someone with an AI background to advance the state of the art in this space.

$184k - $357k

Anduril Industries is a defense technology company transforming U.S. and allied military capabilities with advanced technology. We are seeking a Systems Engineer - Machine Learning to join our rapidly growing team. In this role, you will bridge systems engineering, applied physics, and mathematical and machine learning to solve complex missile defense problems. You will design track-fusion pipelines, build threat-assignment algorithms, and conduct deep sensitivity analyses across complex architectures. This requires proficiency in applied math, physics, and algorithm development using Python or C++, alongside an understanding of sensor data and battle management workflows.

Anduril Industries is seeking a founding Staff AI Infrastructure Engineer to architect, build, and scale the end-to-end machine learning platform that powers the company's autonomous systems. This role will own the technical roadmap for the ML platform, building robust infrastructure, MLOps tooling, and systems architecture to train, evaluate, host, and serve complex AI models. The engineer will optimize experimentation velocity for AI Research Scientists, manage large datasets, and contribute to recruiting and mentoring the infrastructure engineering team.

$220k - $292k

Anduril Industries is a defense technology company focused on transforming military capabilities with advanced technology. We are seeking a Senior AI Infrastructure Engineer to build, scale, and optimize the end-to-end machine learning platform that powers our autonomous systems. In this role, you will own critical components of our ML platform and MLOps tooling, building and operating the infrastructure required to train, evaluate, host, and serve complex AI models across various environments. You will collaborate closely with AI Research Scientists and Platform Engineers to streamline model development, enhance hardware utilization, and ensure the reliable deployment of models into safety-critical operational settings.

$191k - $253k

Anduril Industries is seeking a backend software engineer to own and evolve their internal LLM agent framework. This role is crucial for integrating generative AI systems into the Lattice software platform, enhancing autonomy and reducing cognitive load for users. The engineer will build the platform that enables teams across Anduril to develop, evaluate, and deploy reliable LLM agents in mission-critical environments, working at the intersection of backend infrastructure, applied AI, agent architecture, model post-training, and evaluation tooling.

$220k - $292k

The RL infrastructure team is looking for an engineer to help develop our RL training framework. This role involves designing and implementing the systems that support all RL workloads at SpaceXSI, from small-scale experiments to production training runs. You will be responsible for profiling, debugging, and optimizing the end-to-end training performance, as well as improving the scalability and observability of the RL stack.

$180k - $440k

Together AI

We are seeking a software engineer with a strong focus on reliability to manage the production operations of our Kubernetes-native control plane, which provisions and runs our GPU inference fleet. This platform team develops the API and controllers that enable the inference team to define their needs, such as clusters, model deployments, or capacity changes, and ensures these are reconciled. Your role will be to maintain this functionality in the real world by troubleshooting issues like InfiniBand problems, diagnosing serving faults, and enhancing our automated self-healing systems to permanently resolve recurring failures. The primary goal is to ensure the decoupling remains effective even during disruptions and to maintain fleet efficiency without introducing new instabilities. You will be responsible for inference serving SLOs and error budgets, leading incident response, and implementing lessons learned from postmortems into system changes. Additionally, you will address the reliability aspects of capacity efficiency, recognizing that misconfigured defragmentation or bin-packing can pose production risks. We value candidates with hands-on production reliability experience in large-scale distributed or GPU-serving systems, proficiency in troubleshooting InfiniBand/RDMA and Kubernetes controller-based platforms, and a software engineering approach to GPU infrastructure.

$250k - $320k