What we're looking for :

- Strong hands-on foundation in AI/ML and robotics, including up-to-date robot learning approaches, imitation learning, policy learning, or VLA architectures. You can read a policy-learning paper and also debug a TF tree at 11pm.
- Solid grounding in kinematics, motion planning, and control (MoveIt, OMPL, or equivalent), with Python and C++ fluency in a real-time context where you've written code that runs inside a control loop, not just around one.
- Production or research depth in ROS 2, and simulation environments such as Isaac Sim / Isaac Lab, MuJoCo, Gazebo, or Unity.
- Experience building teleoperation and data-collection pipelines, trajectory capture, dataset curation, and the tooling that makes a demonstration corpus usable for training.
- Demonstrated experience taking a robotics or embodied AI system from prototype to something that ran reliably outside the lab.
- Track record of technical leadership: architecture decisions,



code review culture, and engineers who got better because they worked for you.
- Comfort in front of customers and executives. You can explain a sim-to-real gap to a plant head and a business case to a CXO in the same afternoon.

Bonus points :

- Master's or Ph.D. in Robotics, AI, ML, or a related field.
- Published work in robot learning, manipulation, or locomotion.
- Familiarity with VLA models (OpenVLA, 0, Gemini Robotics class) or LeRobot.
- Deployment under tight hardware constraints: on-device inference, latency budgets, Jetson-class compute.
- Manipulation-heavy experience: grasping, force control, dexterous end-effectors.
- Background in consulting, product innovation, or enterprise AI delivery where you've shipped under someone else's constraints.

📌 Physical AI Engineering Lead (India)
🏢 CRESCENDO GLOBAL LEADERSHIP HIRING INDIA PRIVATE L
📍 India