Reinforcement Learning Jobs

Snorkel AI is seeking a Research Scientist to advance the creation of high-quality data and environments for AI agents. You will build and optimize pipelines that integrate real-world data, automated generation, and human expert input. Collaborating with domain experts, academic partners, customers, and internal teams, you will scale these pipelines to address frontier model performance gaps and enhance data and environment diversity. Your work will empower human knowledge and judgment, enabling experts to refine data and agentic environments, solidifying Snorkel's position as a leader in frontier data solutions. This role is perfect for individuals passionate about advancing frontier AI through data and environment creation, and who enjoy translating research into scalable, reusable systems.

$200k - $375k

Perplexity is seeking an experienced Machine Learning Engineer to advance how AI systems search, reason, and work together to solve complex problems. Our work spans search and retrieval, LLM post-training, multi-agent training, and the harnesses that make these systems effective. We control the full stack, giving us the freedom to develop new approaches across models, agent harnesses, and search infrastructure to use search more effectively, design tools and execution environments around learned behavior, and improve retrieval to support how agents actually work.

NVIDIA is seeking exceptional engineers to design, implement, and deploy cutting-edge end-to-end autonomous driving systems. This role focuses on AI 2.0, leveraging LLMs, VLMs, and VLAs to enhance reasoning, planning, and interactivity in autonomous vehicles and robotics. You will be instrumental in building the future of autonomy by developing and integrating advanced AI models into mass-production vehicles.

$184k - $357k

Sierra is a leading platform for customer-facing AI agents, partnering with major brands to transform customer service and business growth. The Applied Research team focuses on enhancing the quality, speed, and cost-efficiency of AI agents. This involves advancing post-training techniques for open-weight models, pioneering new approaches in voice AI, and translating research breakthroughs into robust production systems. The role involves tackling complex AI and ML challenges, building agents capable of reasoning and executing intricate tasks, and determining the optimal balance between custom models and external intelligence to maximize customer value.

Invisible Technologies is seeking a Research Engineer to join its research organization, focusing on reinforcement learning, evaluation methodology, benchmarks, and RL environments for frontier labs and enterprise clients. This role involves defining how frontier models are measured, with direct influence over the methodology and its implementation. You will translate research questions into practical scoring frameworks, evaluation architectures, or environment designs, and then build the production systems to run them. This is a hands-on role for someone who wants to design the approach and write the code to prove it out, with reporting lines varying by experience level.

Mercor is seeking a Research Scientist Intern to contribute to cutting-edge research in AI. This role focuses on post-training techniques, reinforcement learning with verifiable rewards (RLVR), data generation, and model evaluation. You will investigate how different datasets, rewards, and training methods influence the capabilities and behavior of large language models. The internship involves designing experiments, developing new evaluation methodologies, analyzing model failures, and improving aspects like tool use, agentic behavior, and real-world reasoning. You will collaborate with researchers and domain experts, with the potential for your work to support publications and the development of advanced AI systems.

HUD is building reliable, fair, and open infrastructure for AI data, aiming to make data valuable for creators and trustworthy for AI labs. As a Research Engineer on the Robotics team, you will develop datasets and evaluations crucial for training and assessing embodied AI systems. This role involves translating research needs into data specifications, creating methods for data validation, and conducting experiments to understand how data characteristics impact model performance. You will collaborate with internal research and engineering teams, and potentially with data vendors and buyers, to enhance robotics data offerings.

$100k - $230k

Anthropic

Our team studies how large teams of agents scale to solve complex problems that a single agent cannot, such as rewriting major codebases or formalizing mathematics. We investigate the impact of increasing agent numbers, compute budget, and task length on performance, cost, and coordination. This role bridges research and engineering, involving designing and running large experiments, building the necessary systems, and analyzing surprising results. We aim to move quickly from vague questions to running experiments, developing the platform and evaluations Anthropic uses to measure and manage large agent teams.

$500k - $850k

ClickHouse Labs is an applied research group focused on identifying and solving challenging problems in database systems, with a goal of advancing the state of the art and translating research into real-world system improvements. As a Research Scientist, you will tackle high-impact problems at the intersection of database systems, distributed systems, AI, and systems software engineering. You will collaborate with experienced researchers and engineers on a broad range of topics, including query optimization, execution engines, distributed systems, and emerging agentic workloads, working with leading open-source systems like ClickHouse and PostgreSQL. Your work will involve investigating performance bottlenecks, developing new algorithms and system designs, and evaluating them under realistic conditions, with opportunities to publish your work and contribute to open-source projects.

$175k - $235k

Percepta is transforming critical institutions with applied AI, embedding with industry-leading customers to drive AI transformation. We bring together forward-deployed expertise in engineering, product, and research, along with our in-house toolkit for rapidly deploying agentic workflows and strategic partnerships. As a Research Scientist - Reinforcement Learning, you will work at the intersection of RL research and real-world deployment, advancing decision-making capabilities for critical industries. You will collaborate closely with Embedded Product Managers and engineers to ensure our solutions transform how companies operate.

$200k - $400k

NVIDIA is seeking Senior Deep Learning Scientists to advance our work in streaming and agentic multimodal AI. This role involves developing models capable of reasoning, planning, and acting across diverse modalities, contributing to core algorithmic improvements for multimodal foundation models. You will work on high-impact, large language models and multimodal AI products that enhance user experiences, joining our Nemotron LLM team to tackle real-world agentic AI challenges.

$184k - $288k

NVIDIA is seeking Senior Deep Learning Scientists to advance our work in streaming and agentic multimodal AI. This role involves developing models capable of reasoning, planning, and acting across diverse modalities, with a focus on defining core algorithmic improvements for multimodal foundation models. You will contribute to high-impact, large language models and multimodal AI products that enhance user experiences, working within our Nemotron LLM team.

$152k - $288k

Anthropic

Reinforcement learning (RL) is crucial for Claude's ability to reason, write code, and act autonomously over long horizons. This role is part of the team responsible for building and maintaining the RL training system, which is used to train production models and for researchers across Anthropic to run their experiments. The team collaborates closely with research teams company-wide on the science and engineering required to scale RL effectively. As a Research Engineer, you will be at the heart of RL at Anthropic, with a direct view of RL training at the frontier, as the system you own supports both production and research runs. You will work with collaborators across research teams to understand system performance, identify areas of fragility, and drive future improvements.

$500k - $850k

Moveworks is seeking an Agentic AI Harness Architect to define the technical vision for our agentic AI harness. This role involves planning, selecting tools, managing context, and implementing memory, critique, reflection, adaptation, and recovery mechanisms for AI agents. You will invent and prototype algorithms to enable agents to complete complex tasks with minimal supervision and high reliability. The position requires designing model-agnostic abstractions to integrate foundation models, specialized agents, enterprise tools, and workflows, while developing approaches for agent memory and learning that prioritize enterprise security and privacy. You will also create rigorous benchmarks and evaluation methods for agent performance and explore advanced methods like iterative planning, self-critique, and multi-agent coordination. The role includes building prototypes, identifying promising ideas, and collaborating with platform and product teams to bring them to production, while remaining hands-on with code and experiments.

$201k - $352k

As a Senior Principal Machine Learning Engineer, you will be responsible for designing, developing, and optimizing machine learning models, with a focus on cutting-edge Large Language Models (LLMs), to run efficiently on SambaNova's specialized hardware architecture, including the RDU. This critical role bridges advanced LLM research and practical deployment, involving the development of model architectures, improving training and inference efficiency, and collaborating on hardware-software co-design with compiler, systems, and hardware teams. The engineer will also act as the ML expert, guiding the integration of LLM solutions into production systems and customer-facing products like SambaStack and SambaCloud, with work spanning the full lifecycle from training and inference to evaluation and data curation.

$220k - $300k

HUD is seeking a Product Engineer to transform significant product challenges into tangible user experiences across its AI data platform and marketplace. This role involves collaborating with product, design, engineering, research, and go-to-market teams to identify user pain points in AI data creation and training, define product improvements, and develop solutions. The position blends product strategy, interaction design, and full-stack development, requiring the ability to translate complex technical workflows into clear and user-friendly interfaces while retaining necessary detail.

$100k - $225k

Handshake is seeking a Member of Technical Staff, Evals to help define how frontier AI systems are measured, understood, and improved. This is a high-ownership role for researchers who build, partnering with AI researchers, domain experts, and customers to develop new benchmarks, reward and verifier systems, agent-evaluation methodologies, and data-quality techniques. Early members of the team will have significant influence over technical direction, operating culture, and the open-source software, benchmarks, and research products built. The company prioritizes demonstrated research capability, technical judgment, and a builder's mindset over specific titles, degrees, or career paths.

$200k - $350k

As a Senior Applied AI/ML Scientist on the Search team, you will shape the technical vision, machine-learning algorithm strategy, and system design behind Faire's Search functionality. You will advance real-time search and recommendation systems that power next-generation shopping experiences by working at the frontier of algorithms, combining query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data to return hyper-relevant, personalized products and brands for every user query. This is a chance to influence the end-to-end personalized discovery experience at Faire within a high-scale, deeply multi-modal environment, collaborating closely with a talented team of scientists and engineers.

$211k - $291k

Anthropic

Anthropic is dedicated to building AI systems that are safe, reliable, and steerable, aiming to benefit both users and society. This role is central to advancing Reinforcement Learning (RL), the core technology enabling Claude's reasoning, coding, and autonomous capabilities. The RL Scaling team focuses on how RL performance, stability, and learning efficiency evolve with increasing model size, episode length, and compute power. You will be instrumental in developing and scaling next-generation RL algorithms and architectures, from initial research to large-scale deployment, while deeply understanding and addressing the challenges that arise at scale. This position bridges research and engineering, requiring you to build the systems that accelerate iteration and experimentation, and to tackle complex, unsolved problems in Anthropic's largest RL runs.

$500k - $850k

Anthropic

Reinforcement learning is crucial for training AI models to reason, write code, and act autonomously. At scale, this process involves a demanding distributed system where training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts. This system must continuously exchange data and maintain progress despite hardware failures, shifting loads, and evolving research. The efficiency of this system directly impacts learning outcomes and the speed of research iteration. As a Research Engineer on the Distributed Systems team within RL Engineering, you will focus on the most critical bottlenecks within this system. This could involve areas like scheduling, data movement, sandboxed environment execution, storage, networking, fault tolerance, autoscaling, or observability. The role seeks generalist engineers capable of reasoning from first principles across different system layers and prioritizing impactful problems over familiar ones. The ideal candidate will have experience building and operating large distributed systems, a commitment to detail, and a desire to apply their expertise to a complex, heterogeneous, and rapidly changing workload.

$500k - $850k