Software Engineer, AI for Chip Design
About The Position
OpenAI is seeking a Software Engineer to join the AI for Chips team. This team focuses on applying advanced AI systems to semiconductor engineering, aiming to help engineers develop better chips and shorten design cycles. The role involves building research infrastructure and tooling to enable OpenAI models to design silicon, turning chip-design workflows into reliable environments for reinforcement learning and evaluation, and facilitating researcher experimentation. The position requires strong coding fundamentals, technical judgment, and independent execution. While prior chip-design experience is helpful, domain knowledge can be acquired on the job.
Requirements
- Strong software engineering fundamentals, with experience designing, implementing, and debugging reliable systems.
- Ability to work across a stack, investigate unfamiliar failures, and make practical tradeoffs between speed, correctness, and maintainability.
- Experience independently delivering substantial software projects and ability to explain technical decisions and their impact.
- Comfort working with researchers on evolving requirements and turning open-ended problems into working software.
- Interest in learning how reinforcement learning and chip-design tools fit together.
- Commitment to developing safe, beneficial AI.
Nice To Haves
- 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.
Responsibilities
- Build and maintain infrastructure for reinforcement learning environments, evaluations, and long-running experiments.
- Integrate electronic design automation (EDA) tools into workflows for RTL generation, verification, and physical design optimization.
- Improve experiment reliability, reproducibility, observability, and performance; debug failures across tools, services, and infrastructure.
- Develop tooling and model harnesses that let researchers test ideas quickly and measure correctness and power, performance, and area (PPA).
- Collaborate with researchers and engineers to turn successful experiments into reusable systems and training workflows.
- Own ambiguous projects end to end, communicate progress, and use results to guide the next iteration.
Benefits
- Equal opportunity employer
- Commitment to reasonable accommodations for applicants with disabilities
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
