Machine Learning Engineer - Reinforcement Learning
Core
Build scalable systems for training and fine-tuning large generative models to produce realistic driving behaviors for autonomous vehicle evaluation and scenario coverage.
Role type
Senior IC machine learning engineer (reinforcement learning & generative models)
Builds
Production ML systems for fleet-scale assessment, simulation-aligned RL workflows, and deep learning solutions for human-led triaging and anomaly analysis.
Domain
Autonomous driving, robotics, deep tech
Deliverable
production ML models
Required skills
Reinforcement learning (policy learning, preference/feedback optimization, offline/online pipelines), deep learning, sequence modeling, generative models (LLM/VLM), large-scale distributed training, large-scale data processing, Python, PyTorch
Preferred skills
Autonomous vehicles/robotics background, modern RL and post-training techniques for LLM/dLLM/VLA/video, simulation platform integration, defining metrics for safety-critical AI systems, technical leadership
Technologies
PyTorch, LLM, VLM, simulation platforms
Responsibilities
Build scalable systems for training and fine-tuning large generative models for driving behaviors; Implement and iterate on RL-style methods with reward/preference objectives; Ship deep learning solutions to improve human-led triaging and automate workflows; Own production-oriented ML for fleet-scale assessment; Design and evolve data + evaluation systems inspired by RLHF; Partner with teams to land cross-cutting improvements with clear metrics.
Seniority
Senior, hands-on IC
