Research Scientist Reinforcement Learning Robotics

## About the role and team We are looking for multiple passionate Research Scientists to join the Research Group at Applied Intuition. The mission of the group is to create cutting-edge technology enabling next-generation physical AI, with emphasis on the two most challenging applications reshaping our everyday life: end-to-end autonomous driving and robotic generalist. We have a group composed of leading experts from top institutions and companies, recognized for their exceptional academic and industry contributions—including eight Best Paper awards at premier conferences and journals such as CVPR and ICRA. Learn more at appliedintuition.com/research. Supported by industry-leading tools and infra, researchers can access millions of miles of data from large fleets, and deploy methods they develop into various autonomous and robotic systems including self-driving cars/trucks, autonomous mining/construction machines, humanoid robots and dexterous hands. In addition to your research contributions, you will contribute to and learn from best practices in the autonomy and robotics industries within our fast-paced and customer-focused culture. Improvements deployed to our system immediately help our customers with their programs and deliver value to our business. We are open to all years of experience as long as the necessary requirements are met, including those with potential Tech Lead and Manager capacity. At Applied Intuition, you will: - Conduct research on reinforcement learning (RL) related topics including large-scale closed-loop RL and VLA post-training with applications to robotics with emphasis on dexterous manipulation - Diving into fundamental and relevant topics on RL with broader applications - Work closely with other Research Scientists and interns on research publications for submission to top-tier conferences - Collaborate with Research Engineers and engineering teams to test and deploy algorithms to our autonomy and robotics products We're looking for someone who has: - Strong research record in the fields of RL and VLA post-training for robotics and autonomous systems, with publications in top-tier conferences or journals in the fields of computer vision, machine learning, and robotics - MSc or PhD in machine learning and computer vision with autonomy and robotics applications or closely-related fields - Passion for next-generation, scalable autonomy and robotics for real-world systems - Strong research skills and the ability to work both independently and collaboratively on projects - Technical experience in: Python, Pytorch, computer vision, robotics systems, and distributed machine learning model training Nice to have: Hands-on experience in at least one of the following fields: - VLA post-training for autonomy or robotics - Large-scale closed-loop RL in robotic simulation - Large-scale RL training infrastructure ## What we offer Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment. Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is: $126,000 - $423,000 USD annually.