# Research Engineer, Code RL (Reinforcement Learning) Source: https://realanalystjobs.com/job/research-engineer-code-rl-reinforcement-learning-anthropic-960541bc Research Engineer, Code RL (Reinforcement Learning) at Anthropic, an on-site role based in San Francisco, New York, USA. Pay stated in the posting: $500,000 to $850,000. Posted on 11 June 2026, read from Anthropic's own careers page (Greenhouse), which RealAnalystJobs re-checks daily and removes the role when it closes. The posting says the employer sponsors visas or will consider it. Anthropic has approved H-1B petitions on USCIS record (employer-wide, not a promise for this role). Updated 15 November 2026. ## Key facts - Company: [Anthropic](https://realanalystjobs.com/companies/anthropic) - Location: San Francisco, New York, USA - Work mode: On-site - Pay stated in the posting: $500,000 to $850,000 - Posted: Jun 11, 2026 - Employment type: Full time - Source: Anthropic's careers page (Greenhouse), re-checked daily Skills: [Python](https://realanalystjobs.com/skills/python) ## Visa sponsorship The posting says the employer sponsors visas or will consider it. Confirm with the employer before you apply. Anthropic had H-1B petitions approved for 189 workers in fiscal year 2026 (USCIS). That is history, not a promise for this role. [See the record](https://realanalystjobs.com/companies/anthropic#h1b-record) ## About this role 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 play 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 our latest Claude models. 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 write, edit, test, debug, and ship real software - end to end, on real codebases, with real tools - and to do it correctly, fast, and safely. This role blends research and engineering. You'll design RL environments and coding tasks, build the reward signals and verifiers that capture what "good code" means, run training experiments on frontier models, diagnose why a model does (or doesn't) get better at a class of software-engineering work, and improve the speed and reliability of the pipelines that make all of that iterate fast. Code RL spans several focus areas - from agentic coding behaviors and code correctness, to long-horizon autonomous engineering, to high-performance code for accelerators - and we'll match you to the area where you'll have the most impact. You may be a good fit if you: • Have strong software-engineering skills and deep Python expertise, including async/concurrent programming • Are comfortable owning systems end to end and debugging across the stack • Can balance research exploration with engineering implementation, and engage rigorously in shaping experimental design and interpreting results • Care about code quality, testing, and performance • Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems Strong candidates may also have: • Experience with reinforcement learning, RLHF, post-training, or LLM finetuning • Built coding agents, code-execution sandboxes, eval harnesses, verifiers, or developer tooling • Background in program analysis, testing, verification, compilers, or formal methods • Experience with PyTorch and large-scale distributed training; performance profiling and optimization of ML systems • CUDA / GPU or TPU kernel experience and accelerator-performance intuition • Experience with virtualization and sandboxed code execution environments Related roles If your background leans toward one of these areas specifically, you may also want to look at these postings: • Research Engineer, Performance RL (Reinforcement Learning) - teaching Claude to write correct, fast code for accelerators • Research Engineer, Universes - long-horizon, ultra-realistic agentic training environments • Research Engineer, Cybersecurity RL (Reinforcement Learning) - RL for security-relevant coding capabilities 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: $500,000 - $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. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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 hav Description from Anthropic's public careers feed, reproduced so you can read the role here. Apply on the company's own site; Real Analyst Jobs never submits anything for you. ## How to apply Open [this role on Real Analyst Jobs](https://realanalystjobs.com/job/research-engineer-code-rl-reinforcement-learning-anthropic-960541bc) and use Apply now there to reach the employer's application. The listing is re-checked against Anthropic's careers page daily and removed when it closes. ## Anthropic 11 open analyst roles on Real Analyst Jobs. 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