Machine Learning Engineer - Reinforcement Learning

Job Description

• Build and fine-tune scalable generative models and reinforcement-learning systems for realistic autonomous-driving behaviors, simulation, evaluation, and scenario coverage.
• Develop production-oriented deep-learning solutions, including LLM/VLM applications, RLHF-inspired evaluation loops, and fleet-scale performance assessment systems.
• Train, optimize, monitor, and iterate on ML models that analyze self-driving behavior, automate workflows, and surface critical anomalies across large real-world exposure.
• Requires an M.S. or Ph.D. in Computer Science, Machine Learning, AI, or a related field, or equivalent practical experience; hands-on production ML/RL experience; and experience with distributed training and large-scale data processing.
• Preferred qualifications include autonomous vehicles, robotics or simulation experience; LLM/dLLM/VLA/video-generation post-training knowledge; Python/PyTorch fluency; safety-critical AI metrics experience; technical leadership; and excellent communication.