Physical AI Lab

 

 

About the Role

At WIN Labs, we're creating intelligent robotic systems that can perceive, reason, and act in the real world. From multi-robot coordination and agentic AI to Sim2Real learning and autonomous manipulation, our teams are pushing the boundaries of what's possible in industrial robotics.

We're launching a new Physical AI Lab in Mountain View, California, and looking for a hands-on engineer who loves building, experimenting, and deploying real robotic systems. This lab serves as WIN Labs' US innovation hub, bringing cutting-edge research to life through live demonstrations, customer engagements, rapid experimentation, and real-world deployments.

You'll work closely with our core Robotics & Embodied AI team in Bengaluru while helping establish and grow our Mountain View presence. If you're excited about robotics, autonomy, foundation models, and seeing your code come alive on real hardware, we'd love to talk.

Physical AI • ROS 2 • Isaac Sim • Isaac Lab • MuJoCo • Agentic AI • Vision-Language-Action Models • Multi-Agent Systems • Open-RMF • PyTorch • Docker • FastAPI • NVIDIA Omniverse • Humanoids • Mobile Manipulators • Quadrupeds • AMRs • Reinforcement Learning • Sim2Real

• Deploy and extend Sim2Real pipelines developed by our Bengaluru team, validating AI models on real robotic hardware.

• Build agentic robotic systems that transform high-level goals into perception, planning, and action workflows.

• Bring multi-robot coordination solutions to life using fleet management, task allocation, and collaborative autonomy frameworks.

• Develop robust ROS 2 software stacks integrating perception, planning, and control systems.

• Apply classical robotics fundamentals including kinematics, dynamics, motion planning, state estimation, and control theory to build reliable autonomous systems.

• Integrate AI services, APIs, cloud infrastructure, and robotics platforms into scalable solutions.

• Design and showcase compelling customer demonstrations that highlight the latest advances in Physical AI.

• Drive experiments from idea to real-world validation and share findings with the broader robotics team.

• Collaborate daily with world-class robotics engineers and researchers across Mountain View and Bengaluru.

• Represent WIN Labs at conferences, customer meetings, industry events, and innovation forums.

• Help establish and grow a state-of-the-art robotics lab, including managing robot platforms, hardware inventory, and vendor relationships.

• Bachelor's or Master's degree in Robotics, Computer Science, Electrical Engineering, or a related field (PhD is a plus).

• 3+ years of hands-on robotics software engineering experience.

• Strong programming skills in Python and C++.

• Deep experience with ROS/ROS 2 and robotics simulation platforms such as Isaac Sim, MuJoCo, or Gazebo.

• Experience deploying robotics or autonomy solutions beyond research prototypes.

• Hands-on experience with Sim2Real techniques, domain randomization, synthetic data generation, or system identification.

• Experience building or integrating LLM-based agentic systems, Vision-Language-Action (VLA) models, or AI-powered robotic applications.

• Strong understanding of machine learning and deep learning frameworks such as PyTorch.

• Experience with Docker, CI/CD, Git, APIs, and cloud-native development.

• A builder mindset with a track record of taking ideas from concept to deployment.

• Experience with multi-robot systems, Open-RMF, fleet management, or multi-agent reinforcement learning.

• Hands-on experience with industrial arms, mobile manipulators, humanoids, quadrupeds, drones, or AMRs.

• Familiarity with NVIDIA's robotics ecosystem, including Isaac Sim, Isaac Lab, Replicator, or related tools.

• Experience with sensor fusion, SLAM, 3D perception, and computer vision systems.

• Experience scaling simulation workloads on cloud or GPU infrastructure.

• Knowledge of data engineering, SQL/NoSQL databases, and robotics data pipelines.

• Experience designing end-to-end robotics solutions for real-world deployments.

• Publications, patents, open-source contributions, or competitive robotics achievements.