Applied Intuition
Research Engineer - Reinforcement Learning, Self-Driving
$126K–$423K
Sunnyvale · On-site · Full-time · Posted Feb 13, 2026
- Experience
- At least 1 year in autonomy applications or a closely related field; open to all years of experience otherwise.
- Education
- Master's or PhD in machine learning and computer vision with autonomy and robotics applications, or a closely related field.
About the job
Research reinforcement learning methods and infrastructure for autonomous driving and robotics, publish research, and deploy algorithms and simulation tools into autonomy systems.
What you'll do
- Research reinforcement learning and training infrastructure, including self-play, VLA post-training, and closed-loop RL.
- Collaborate on research publications for top-tier conferences.
- Work with engineering teams to deploy autonomy algorithms and develop neural simulation and generation tools.
What they ask for
- Hands-on experience in at least one listed area: self-play RL and imitation or behavior learning; VLA post-training; large-scale closed-loop RL in driving simulation; or large-scale RL training infrastructure.
- Technical experience in Python, Pytorch, computer vision, robotics systems, and distributed machine learning model training.
- Master's or PhD in machine learning and computer vision with autonomy and robotics applications, or a closely related field.
- At least 1 year of experience in autonomy applications or a closely related field.
Nice to have
- Ray for large-scale RL training infrastructure.
- Passion for building and shipping customer-focused software frameworks or tools.
Pay
$126K – $423K (base salary)
Tools
Python, Pytorch, Ray
AI focus
Research and apply reinforcement learning for autonomous driving and robotics, including self-play RL, VLA post-training, large-scale closed-loop RL, and neural simulation.
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