Applied Intuition
Research Engineer - Reinforcement Learning, Self-Driving
About this role
Applied Intuition seeks Research Engineers to advance reinforcement learning and training infrastructure for autonomous driving and robotics. You'll conduct cutting-edge research on large-scale self-play RL and closed-loop simulation while collaborating with world-class researchers and deploying algorithms to production systems serving top global automakers and defense organizations.
What you'll do
- Conduct research on reinforcement learning, self-play RL, and large-scale closed-loop RL for autonomous driving applications
- Develop and optimize RL training infrastructure for neural simulation and VLA post-training
- Collaborate with Research Scientists and interns to produce high-quality publications for top-tier conferences
- Partner with engineering teams to deploy end-to-end algorithms for production autonomous vehicles
- Work on neural simulation and generation tools supporting autonomy development
- Contribute to best practices in autonomy and robotics within a customer-focused environment
What they're looking for
- Reinforcement learning (self-play, imitation learning, behavior learning)
- Large-scale RL training infrastructure (Ray experience preferred)
- Python and PyTorch
- Computer vision
- Distributed machine learning
- Robotics systems
- Closed-loop RL simulation for driving
- VLA post-training for autonomy
Benefits
- Base salary, equity (options/RSUs), and comprehensive health/dental/vision insurance
- Life and disability insurance coverage
- 401k retirement plan with employer match
- Learning and wellness stipends
- Paid time off
- Flexible work arrangements with primary in-office presence in Sunnyvale
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Applied Intuition
Applied Intuition builds autonomous vehicle and defense systems software, including motion planning algorithms, simulation infrastructure, and autonomy integration platforms for aerial and ground platforms. The company is hiring for security engineers, robotics/autonomy software engineers, hardware-in-the-loop specialists, and IT operations professionals to support its growing physical AI operations.
- Website
- appliedintuition.com
Likely interview questions
- Can you describe your hands-on experience with self-play RL, imitation learning, or VLA post-training? What specific projects or papers have you worked on in these areas?
- Tell us about your experience with large-scale RL training infrastructure. Have you worked with Ray or similar distributed training frameworks, and what challenges did you encounter?