About this role
Engineers who enjoy operating autonomously across ambiguous problem spaces and collaborating closely with researchers will find a strong fit within this team. OpenAI is connecting advanced AI models with semiconductor engineering to shorten design cycles and help build better chips.
Software engineers in this group build the research infrastructure and tooling that enable AI models to design silicon. Daily work involves turning complex chip-design workflows into reliable environments for reinforcement learning and evaluation, integrating electronic design automation tools, and building model harnesses that measure performance and correctness.
The role exists to bridge hardware expertise with model training and research, requiring strong coding fundamentals and clear technical judgment. Prior chip-design experience is helpful, but candidates can learn that domain alongside hardware specialists on the team.
What you will do
- Build and maintain infrastructure to support reinforcement learning environments, evaluations, and long-running experiments.
- Integrate electronic design automation tools into workflows for RTL generation, verification, and physical design optimization.
- Improve experiment reliability, reproducibility, observability, and performance while debugging failures across tools and services.
- Develop tooling and model harnesses that allow researchers to test ideas quickly and measure correctness and power, performance, and area.
- Collaborate with researchers and engineers to turn successful experiments into reusable systems and training workflows.
- Own ambiguous projects from end to end, communicate progress clearly, and use results to guide subsequent iterations.
What you need
- Possess strong software engineering fundamentals with demonstrated experience designing, implementing, and debugging reliable systems.
- Demonstrate the ability to work across a technology stack, investigate unfamiliar failures, and make practical tradeoffs between speed, correctness, and maintainability.
- Have independently delivered substantial software projects while explaining technical decisions and their impact.
- Show comfort working alongside researchers on evolving requirements and turning open-ended problems into working software.
- Maintain an interest in learning how reinforcement learning and chip-design tools fit together alongside a care for developing safe artificial intelligence.
Nice to have
- Experience with research infrastructure, distributed systems, experiment orchestration, or ML tooling.
- Familiarity with reinforcement learning, model evaluations, or training workflows.
- Experience with Python, containerized tools, and reproducible development environments.
- Experience with RTL, Verilog/SystemVerilog, EDA tools, formal verification, or chip-design automation.
Benefits
- Offers Equity
Skills and tech stack
Questions candidates ask
What is the salary range for this position?
The salary range for this role is $266K to $468K and includes equity offers.
Where is the role located?
This position is based in San Francisco.
Do I need prior chip-design experience to apply?
Prior chip-design experience is helpful, but candidates can learn the domain alongside the team's hardware specialists.
Are there any legal status requirements for applicants?
To comply with U.S. export control laws and regulations, candidates may need to meet certain legal status requirements as provided in those laws.