Research Engineer - Robot Learning

Responsibilities

• Support robotic and data collection hardware setup and design mechatronic systems for customized demands
• Construct robotic simulation environments at scale for reinforcement learning (RL) training
• Process human data for various robotic use cases
• Collaborate with Research Scientists and interns to produce high-quality research for top-tier conferences
• Partner with engineering teams to deploy end-to-end algorithms for mass production vehicles and neural simulation tools

Requirements

• Hands-on experience in one or more of the following: world-action foundation models, video/Gaussian generation, diffusion policy, multi-modal robot learning, VLA post-training, reinforcement learning, physics-aware reconstruction, or deformable simulation
• Strong engineering and research skills with the ability to work both independently and collaboratively
• Technical proficiency in Python, PyTorch, computer vision, robotics systems, and distributed machine learning model training
• A passion for developing next-generation, scalable autonomy and robotics for real-world systems

Preferred Qualifications

• MSc or PhD in machine learning, computer vision, or a closely related field with autonomy and robotics applications
• Industry experience in relevant domains, particularly self-driving applications
• Experience building and shipping customer-focused software frameworks or tools

About the Company

Applied Intuition is powering the future of physical AI. Founded in 2017, we are creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. We service the automotive, defense, trucking, construction, mining, and agriculture industries through tools, operating systems, and autonomy solutions. Our technology is trusted by eighteen of the top 20 global automakers and the United States military.