Research Engineer - Post-Training

Responsibilities

• Post-train frontier models to autonomously perform complex tasks across the semiconductor design and verification pipeline.
• Propose and optimize chip architectures.
• Generate and refine RTL code.
• Run simulations.
• Identify verification gaps and iteratively improve designs.
• Collaborate with hardware design, verification, and computer architecture experts to design reinforcement learning environments.
• Develop structured reward functions, scaling strategies, and evaluation frameworks.

Requirements

• Experience creating and scaling RL environments for LLMs or multimodal agents.
• Building high-quality evaluation datasets and benchmarks for complex reasoning or design tasks.
• Working closely with domain experts in hardware and verification to define evaluation metrics, constraints, and simulation conditions.
• Designing reward functions and feedback pipelines that balance correctness, performance, and design efficiency.
• Running large-scale RL fine-tuning or post-training experiments for frontier models.
• Applying reinforcement learning or curriculum learning to structured reasoning or symbolic domains.