AI Resident

Job description

Job responsibilities

• Conduct research and build systems for embodied physical intelligence
• Develop and evaluate methods in VLA, World Models, World Action Models, simulation, and RL
• Design and run experiments on robotics tasks involving perception, planning, control, and long-horizon behavior
• Build training and evaluation pipelines for large-scale embodied learning systems
• Work closely with research and engineering teams to move ideas from prototype to real or simulated robot platforms
• Explore how multimodal foundation models can improve robot capability in real deployment settings
• Contribute to technical reports, internal research discussions, and, where appropriate, publications

Job requirements

• PhD student, recent graduate, or early-career researcher/engineer in Computer Science, Robotics, Machine Learning, Electrical Engineering, or a related field
• Experience with modern ML frameworks such as PyTorch, JAX, or TensorFlow
• Experience using AI-assisted coding tools and agentic development workflows to prototype, iterate, and build quickly
• Ability to implement, debug, and evaluate research ideas in a fast-moving environment
• Strong engineering judgment, including the ability to validate, refine, and productionize AI-assisted code
• Rich hands-on experience in robotic manipulation, mobile manipulation, or industrial robotics
• Experience training, fine-tuning, or evaluating multimodal or embodied models
• Experience with World Models, action-conditioned prediction, model-based learning, planning, or control