Senior Machine Learning and Simulation Engineer, Autonomous Vehicles

What you'll do

• Lead the design and development of large-scale RL training frameworks for multi-modal AV foundation models.
• Build and optimize simulation and data processing pipelines to enable scalable training of driving policies.
• Measure and enhance simulation quality while refining reward functions for RL training.
• Develop robust monitoring and debugging tools to ensure training workflow reliability on large GPU clusters.
• Integrate state-of-the-art model architectures into efficient and scalable training pipelines with researchers.
• Design and improve the accuracy of closed-loop simulation frameworks using SOTA technologies like NuRec and Cosmos.

What we're looking for

• Bachelor's degree in Computer Science, Robotics, Engineering, or a related field (or equivalent experience).
• 12+ years of relevant professional experience in large-scale ML training, AV systems, simulation, and AI infrastructure development.
• Deep proficiency in RL algorithms, including PPO and GRPO, with experience in hyperparameter tuning and reward function design.
• Exceptional programming skills in C++ and Python for developing efficient systems and data pipelines.
• Extensive experience with large-scale GPU clusters, High-Performance Computing (HPC) environments, and job scheduling tools like Kubernetes or SLURM.
• Experience in RL infrastructure or general LLM training/fine-tuning infrastructure in industry (preferred).
• Experience in simulation and closed-loop evaluation of autonomous driving end-to-end models (preferred).
• Proven record on large-scale data pipeline development and algorithm optimization (preferred).