Applied Scientist III — Robotics & Physical AI, Autonomous Lab, WW Sustainability
Core
Building and operating the first autonomous materials discovery laboratory using robotics and Physical AI to generate scientific results and validate AI-driven hypotheses on real hardware.
Role type
Senior IC Applied Scientist (Robotics & Physical AI)
Builds
Autonomous experimental workflows integrating dexterous robotic platforms, analytical instruments, and AI-driven hypothesis generation into a closed-loop discovery pipeline.
Domain
Materials science, robotics, Physical AI, sustainability
Deliverable
production ML models
Required skills
motion planning, control, platform integration, vision-language-action models, sim-to-real transfer, agentic orchestration, policy training, reinforcement learning, imitation learning, active learning, Bayesian optimization
Preferred skills
sim-to-real transfer experience, VLA or robot policy architectures, collaborative robot platforms, agentic AI systems, self-driving laboratory systems
Technologies
C/C++, Python, Java, Perl, MxNet, Tensor Flow, OpenVLA, π0, RT-2, SiLA 2
Responsibilities
Develop, train, and benchmark robotic manipulation policies for materials synthesis and characterization; Design and execute sim-to-real transfer strategies; Integrate robotic platforms and laboratory instruments into automated workflows via APIs; Architect policy training pipelines combining teleoperation data, synthetic demonstrations, reinforcement learning, and imitation learning; Build production-grade agentic runtime systems; Design and execute autonomous experimental campaigns applying active learning, Bayesian optimization, or RL; Drive technical design reviews and set scientific direction for the autonomous lab platform.
Seniority
Senior, hands-on IC
