Research Engineer - Reinforcement Learning, Self-Driving

About the Company

Applied Intuition is powering the future of physical AI. Founded in 2017, the company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet, servicing the automotive, defense, trucking, construction, mining, and agriculture industries.

Responsibilities

• Conduct research on reinforcement learning (RL) and its training infrastructure, including large-scale self-play RL, VLA post-training, and large-scale closed-loop RL based on neural simulation
• Work closely with Research Scientists and interns on high-quality research publications for top-tier conferences
• Collaborate with engineering teams on ADAS, data, and simulation to deploy end-to-end algorithms for mass production vehicles
• Develop neural simulation/generation for tools supporting autonomy development

Requirements

• Hands-on experience in self-play RL, imitation learning, or behavior learning
• Experience with VLA post-training for autonomy or robotics
• Experience with large-scale closed-loop RL in driving simulation
• Experience with large-scale RL training infrastructure (Ray preferred)
• Proficiency in Python and PyTorch
• Technical experience in computer vision, robotics systems, and distributed machine learning model training
• Strong engineering and research skills

Preferred Qualifications

• MSc or PhD in machine learning, computer vision, or a closely related field
• Industry experience in self-driving applications
• Passion for building and shipping customer-focused software frameworks or tools