Research Engineer, AI for Chip Design

📋 Description

• Build RL environments and evaluations for tasks such as RTL generation, design verification, and
• Develop and test approaches that help models use chip-design tools and improve power, performance
• Design experiments, establish baselines, and measure whether improvements hold up on new tasks and
• Investigate failures across model behavior, rewards, evaluation tools, and experiment
• Improve iteration speed through better tooling, faster evaluations, and proxy rewards that reflect
• Turn successful experiments into reusable research code and training workflows, working closely

🎯 Requirements

• Strong programming and debugging skills and a track record of turning technical ideas into working
• Experience with reinforcement learning, model evaluations, post-training, or other applied ML
• Experience building tool-using agents, reward functions, or automated evaluation systems.
• Ability to form clear hypotheses, design useful experiments, and distinguish meaningful results
• Work independently on ambiguous problems and make practical decisions about what to build or test
• Stay close to the implementation and can explain what you built, what failed, and what you learned.