The opportunity
OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering.
What you'll do
Build RL environments and evaluations for tasks such as RTL generation,: design verification, and physical design optimization.
Develop and test approaches that help models use chip-design tools and: improve power, performance, and area while preserving correctness.
Design experiments, establish baselines, and measure whether improvements hold up on new tasks and designs.
Investigate failures across model behavior, rewards, evaluation tools, and experiment infrastructure.
Improve iteration speed through better tooling, faster evaluations, and proxy: rewards that reflect the outcomes we care about.
Turn successful experiments into reusable research code and training: workflows, working closely with researchers and engineers.
What they're looking for
- Have strong programming and debugging skills and a track record of turning: technical ideas into working software.
- Experience with reinforcement learning, model evaluations, post-training, or other applied ML research.
- Experience building tool-using agents, reward functions, or automated evaluation systems.
- Can form clear hypotheses, design useful experiments, and distinguish: meaningful results from noise or evaluation errors.
