2027 Summer Intern, PhD, Machine Learning - Simulation & Closed-Loop Training

📋 Description

• Design, implement, and scale Reinforcement Learning post-training and distillation algorithms (such
• Develop learned reward models, realism critics, and discriminators within a closed-loop multi-agent
• Run rigorous closed-loop ablation studies on large-scale TPU clusters—leveraging agentic
• Write clean, modular, and well-tested JAX code in core simulation and autonomous driving codebases

🎯 Requirements

• Currently pursuing a PhD in Computer Science, Machine Learning, Robotics, or a related technical
• Core Implementation Fluency (Mandatory): Strong tensor implementation and debugging skills in
• Deep Research Expertise in Either (a) Reinforcement Learning & Post-Training (hands-on research

🎁 Benefits

• Participation in the Company’s generous benefits programs, subject to eligibility requirements