Reinforcement Learning Jobs

As a Research Scientist at Mercor, you will work at the intersection of research and engineering on frontier post-training. You will develop new training and evaluation methods, test them through rigorous experiments, and implement successful approaches at scale. Working with researchers, engineers, domain experts, and customers, you will investigate how data, rewards, environments, and optimization methods shape model behavior. Your work will influence frontier models, Mercor’s products, and the broader research community through releasing blogposts, technical reports, and papers.

$250k - $500k

Thinking Machines is building AI that extends human will and judgment, with a focus on training frontier models and developing tools that allow users to customize AI for their unique needs. This role leads the Fine-tuning Science team, focusing on frontier customization techniques and the Tinker post-training engine. It's a player-coach position where you will remain hands-on with scientific research while also guiding the team, shaping its direction, and ensuring research findings are integrated into Tinker. You will collaborate with internal research teams, contribute to open science, and engage with external users.

$350k - $475k

Abundant is an applied research lab focused on scaling reinforcement learning for safe and reliable agentic capabilities. As a Member of Technical Staff, Alignment, you will be instrumental in ensuring that alignment is a core component of all our work, from the code we deploy and the runbooks we write to the papers we publish. This role involves testing models in advanced environments, identifying and mitigating potential risks like reward hacking and deception, and building robust tools to monitor and secure AI agents.

$250k - $450k

Anthropic

The Encodings Infra team at Anthropic maintains the libraries that engineers and researchers use to encode text and multimodal data for Claude. This team also defines Claude's prompt structure, including how user turns are represented and how Claude interacts with tools. As a Software Engineer on this team, you will be responsible for the design and upkeep of these libraries, ensuring their APIs are intuitive, performance is optimized, and abstractions are robust. Your work will span across various systems, from pretraining to finetuning and the API, requiring close collaboration with researchers and engineers to facilitate the rapid transition of new encoding ideas from experimentation to production.

$320k - $405k

SpaceXAI is building Super Intelligence to help humanity understand the universe, from supercomputers to Grok models and their suite of applications. The RL Environments team is seeking a Software Engineer to build systems that transform real-world data into high-quality environments and tasks for reinforcement learning. This role involves creating more realistic training environments and owning the platforms and quality layers for trustworthy data production at scale. You will collaborate closely with ML Platform and research teams to convert various data sources into training-ready environments, making high-quality RL data more accessible for model training efforts.

We are building the AI layer of the Radio Access Network, applying agentic AI, machine learning, and LLMs to real RAN challenges. This role is for a Technical Lead to own the end-to-end architecture and technical direction of these AI systems. It is a hands-on senior individual contributor role, combining architecture, coding, technical leadership, and mentorship. You will work alongside RAN, PHY, and software teams, building production-grade AI solutions for real cellular networks.

We are seeking a motivated engineer to enhance the integration of APIs across our CUDA-X math library software stack into modern LLM and agentic AI workflows. Organizations worldwide leverage GPU-powered data centers for AI, data analytics, and scientific simulations, driving progress in fields like LLMs, computer vision, and autonomous vehicles. Our team develops the essential GPU-accelerated libraries and SDKs for these technologies. In this role, you will ensure that human engineers and AI agents can easily build high-performance applications by effectively utilizing CUDA-X libraries. We are looking for individuals with a unique combination of technical expertise, developer experience, and communication skills.

$152k - $288k

NVIDIA is at the forefront of the AI revolution, exploring the next frontier of Physical AI, which involves machines that can perceive, reason about, and act within the three-dimensional world. The NVIDIA Cosmos platform provides open foundation models for Physical AI, designed to interpret images, video, and text to create a structured understanding of physical scenes, including motion, object interactions, geometry, and physical context. These models serve as the reasoning layer for robots, autonomous vehicles, and smart infrastructure. The Cosmos Engineering team is responsible for developing the core capabilities behind these models and is seeking a Senior Deep Learning Engineer to lead the data engine and end-to-end training verification for 3D spatial reasoning and perception. This role involves ensuring models accurately learn and represent 3D spatial concepts, working closely with research scientists to translate hypotheses into measurable capabilities in shipped models, and focusing on the critical role of data and evaluations in achieving frontier model quality.

NVIDIA is seeking a scientist at the intersection of quantum device physics, quantum calibration, and machine learning to help accelerate the quantum ecosystem. This role will focus on designing and building real-time models that learn from device physics, calibration experiments, decoding, and system performance. You will develop physics-informed data synthesis pipelines, post-trainable model architectures, and practical benchmarks for the quantum community. Your research will translate qubit physics and the quantum control stack into performant AI systems for fault-tolerant quantum computing, spanning synthetic training data generation, surrogate modeling, and co-optimized calibration-decoding pipelines. You will collaborate with teams across Product, Engineering, and Applied Research to push the frontier of Accelerated Quantum Supercomputers.

$192k - $305k

Artisan is building a new, ambitious project at the frontier of agentic AI, pushing the boundaries of what AI agents can achieve. This role is for a hands-on technical lead responsible for designing and building the core AI architecture, focusing on agent behavior, multi-agent systems, tool use, context management, and evaluation. The position offers broad technical ownership as an individual contributor, involving consequential architecture decisions, writing critical system components, and close collaboration with existing engineers and leadership. The ideal candidate enjoys tackling uncertain problems and executing detailed engineering to deliver robust solutions.

$250k - $325k

AfterQuery is an applied research lab focused on curating data solutions for foundation model development, serving frontier AI labs with the mission of making expertise widely accessible. This is a unique opportunity to join a rapidly growing company at a pivotal moment in AI. We are backed by leading investors and have a strong founding team with experience from top tech and finance companies. We are seeking exceptional undergraduate and masters students for our AI/ML Research Internship program to work on cutting-edge AI projects in advanced reasoning, computer use, and agentic models. Interns will have access to expert networks and specialized datasets, with opportunities to co-author research papers and present at leading AI conferences.

OpenAI

We’re hiring a Research Engineer to help OpenAI models solve chip-design problems through reinforcement learning, tool use, and evaluation. You’ll own experiments from the initial idea through implementation and analysis, building environments and evaluations, running training, investigating failures, and using the results to decide what to try next. You’ll also build the software needed to make those experiments reliable and reproducible. We value strong coding fundamentals, careful experimental judgment, and the ability to make progress independently. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists.

$380k - $500k

The Agent Capabilities team at Perplexity Computer is at the forefront of agentic AI, bridging frontier AI research with product innovation. This team builds the foundational capabilities that empower users and agents to tackle increasingly complex tasks. They are responsible for translating cutting-edge AI model breakthroughs into reusable product features, evaluating emerging model capabilities, identifying user value, and transforming these into reliable, scalable, high-quality experiences. This role offers broad ownership at the intersection of AI research, agent systems, platform engineering, and product innovation.

$220k - $405k

Abundant is building the NVIDIA of training data, recognizing the critical need for scaling data as AI models advance beyond supervised learning to reinforcement learning and learning from experience. The founding team brings extensive experience from leading AI organizations, with a proven track record in deploying deep learning models at scale, training state-of-the-art models, and managing large data pipelines. As a Member of Technical Staff, you will collaborate directly with the founding team to architect the future of model reasoning and intelligence, working at the intersection of research and execution to push the boundaries of AI capabilities.

$120k - $120k

NVIDIA is seeking a Principal EDA R&D Engineer to lead the research, architecture, and development of next-generation hardware formal verification tools. This role involves pioneering advancements in core formal verification engines, enhanced by Agentic AI frameworks. You will craft collaborative, autonomous AI agent networks to extend formal tools, enabling them to automatically break down large builds, coordinate solver strategies, synthesize complex properties, and debug execution traces at an unprecedented scale. The position demands deep algorithmic knowledge, rigorous industrial software engineering, and a proven track record of delivering production-grade EDA tools.

$232k - $368k

OpenAI

We are seeking a Software Engineer to develop the research infrastructure and tooling that will enable OpenAI models to design silicon. This role involves transforming chip-design workflows into robust environments for reinforcement learning and evaluation, and simplifying the process for researchers to conduct experiments and iterate on new ideas. You will bridge software engineering, tool integration, and open research challenges, leveraging strong coding fundamentals, clear technical judgment, and independent execution. While prior chip-design experience is beneficial, domain knowledge can be acquired alongside our hardware specialists.

$266k - $468k

Anthropic

At Anthropic, we are pioneering new frontiers in AI that have the potential to greatly benefit society. However, developing advanced AI also comes with risks if not properly safeguarded. As a Research Engineer, you'll help to safely advance the capabilities of our models in incident response, security analysis, vulnerability remediation, and other areas of defensive cybersecurity. This role blends research and engineering, requiring you to both develop novel approaches and realize them in code. Your work will include designing and implementing RL environments, conducting experiments and evaluations, delivering your work into production training runs, and collaborating with other researchers, engineers, and cybersecurity specialists across and outside Anthropic. This role requires ML experience combined with domain expertise in cybersecurity. You might be an ML researcher with a history of cybersecurity work, or a security professional with a background in ML.

Decagon is seeking a Research Engineer focused on Safety to ensure the reliability and controllability of their AI agents. This role involves identifying real-world failure modes and developing the necessary models, evaluations, and safeguards to prevent them. The ideal candidate will be a strong engineer passionate about advancing applied AI safety in production, with the ability to own projects end-to-end and make high-impact technical decisions.

$200k - $400k

Decagon is seeking a Senior Research Engineer focused on Safety to ensure the reliability and controllability of their AI agents. This role involves identifying real-world failure modes and developing the necessary models, evaluations, and safeguards to prevent them. The ideal candidate will be a strong engineer passionate about advancing applied AI safety in production, taking ownership of their work from end-to-end, and making high-impact technical decisions.

$200k - $400k

NVIDIA is seeking a Principal Scientist to lead the technical direction for synthetic data generation across its frontier model initiatives. This role involves defining and building open-source libraries within the NVIDIA NeMo ecosystem to create synthetic datasets for text, code, structured, and multimodal data. These datasets will be crucial for the pre- and post-training of large language models like Nemotron. The position blends hands-on software engineering with applied research in generative methods, requiring collaboration with various internal teams and external research labs.

$272k - $431k