Research Engineer, Chip Design RL (Reinforcement Learning

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 design silicon. Hardware design is difficult and unforgiving – exactly the sort of domain we want Claude to excel at. You'll leverage your chip design expertise and turn it into tasks and signals for models to learn from. Specifically, you will:

• Invent, design, and implement RL environments and evaluations for agentic RTL generation, design verification (including formal) verification, physical design optimization.
• Work on cross-cutting RL considerations such as EDA-tool latency optimization and proxy rewards.
• Conduct experiments and shape our roadmap.
• Deliver your work into research and production training runs.
• Collaborate with other researchers and engineers across and outside Anthropic.

You may be a good fit if you:

• Have expertise in ASIC or FPGA design: RTL, design verification (UVM, formal methods, coverage-driven), physical design (synthesis, place-and-route, timing closure), PPA optimization, DFT, ECOs.
• Are fluent with industry EDA tools and processes.
• Have taped out chips and have experience going from spec to silicon.
• 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, evaluations or environments.
• Built tooling or automation around chip design flows.
• Worked on ML accelerators or high-performance compute hardware.
• Familiarity with high-level synthesis or architecture simulators.

The annual compensation range for this role is listed below.

Annual Salary: $500,000 —$850,000 USD

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.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from  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  directly for confirmed position openings.

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.

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.