What we're looking for
Solid hands-on foundation in AI/ML and robotics, including contemporary robotb 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 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 you've shipped under someone else's constraints.

📌 Physical Ai Engineering Lead Bengaluru
🏢 Crescendo Global Leadership Hiring India
📍 Bengaluru