Research Engineer - Reinforcement Learning, Self-Driving
Conducts research on reinforcement learning for self-driving cars and robotics, develops large-scale RL training infrastructure, and deploys algorithms to production systems. Requires hands-on RL experience, PyTorch/Python proficiency, and strong research skills.
About the job
Responsibilities
- Conduct research on reinforcement learning (RL) and its training infrastructure, including large-scale self-play RL, VLA post-training, large-scale closed-loop RL based on neural simulation with applications to autonomous driving.
- Work closely with Research Scientists and interns on high-quality research publications to submit to top-tier conferences.
- Collaborate with engineering teams on ADAS, data, and simulation to deploy end-to-end algorithms for mass production vehicles, and neural simulation/generation for tools supporting autonomy development.
Requirements
- Hands-on experience in at least one of: self-play RL and imitation learning, behavior learning; VLA post-training for autonomy or robotics; large-scale closed-loop RL in driving simulation; large-scale RL training infrastructure (Ray preferred).
- Passion for next-generation, scalable autonomy and robotics for real-world systems.
- Strong engineering and research skills and ability to work independently and collaboratively.
- Technical experience in: Python, PyTorch, computer vision, robotics systems, and distributed machine learning model training.
Nice to Have
- Industry experience on relevant topics (self-driving application preferred).
- MSc or PhD in machine learning and computer vision with autonomy and robotics applications or closely related field.
- Passion for building and shipping customer-focused software frameworks or tools.
Compensation
Base salary range: $126,000 - $423,000 USD annually, plus equity and benefits.
Skills
Reinforcement Learning, PyTorch, Python, Computer Vision, Ray, Imitation Learning, Distributed Machine Learning, Robotics, Self-Play Rl, Vla
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