Conduct original research in embodied AI, including learning from warfighter demonstration, reinforcement learning, memory, reward, vision-language modeling, and world modeling
Build, test, and benchmark large-scale models for perception, decision-making, and control in simulated and physical environments
Investigate transfer learning and continual learning paradigms across diverse robotic domains
Collaborate with engineering, robotics, and field teams to integrate research into operational systems
Lead research strategy and roadmap across key areas of autonomy and machine learning
Support field tests and data collection campaigns to evaluate system performance in realistic environments

PhD in Computer Science, Robotics, Machine Learning, or a related field plus 4+ years of applied research experience (industry, postdoc, or lab), or 8+ years of equivalent industry research experience without a PhD
Strong publication record in top-tier venues
Deep expertise in one or more of the following: reinforcement learning, imitation learning, vision-language models, sim-to-real, world modeling, or agentic AI
Hands-on experience building and evaluating models for embodied agents or autonomous systems
Proficiency in Python and frameworks such as PyTorch, TensorFlow, or JAX
Experience working with large-scale datasets and high-dimensional sensor inputs
Demonstrated ability to take ideas from research concept to deployed prototype
Must be a U.S. Person due to required access to U.S. export controlled information or facilities

Senior AI Researcher

Key skills