About the Role:

We are seeking a Robotics Architecture Manager, who can lead technical development, mentor engineers, and drive end-to-end robotics solution delivery. The ideal candidate brings 15+ years of overall industry experience and 5+ years of core robotics experience, with proven strength in perception, planning, control, simulation, and ROS/ROS2 architecture, and a track record of deploying robotics solutions at scale.

Roles & Responsibilities:

- Lead and mentor a robotics development team, providing technical guidance on ROS/ROS2 architecture and reviewing deliverables.

- Design and implement robotics solutions using simulation platforms such as NVIDIA Omniverse, Isaac Sim, and MuJoCo.

- Develop perception modules using computer vision, 3D point cloud processing, and sensor fusion techniques.

- Implement motion planning, SLAM, navigation, and robot control algorithms for mobile and collaborative robots.

- Build and optimize AI/ML models (DL/RL) for robotic autonomy and deploy them on edge/embedded platforms.

- Develop robotics software in Python and C++ using ROS2 and modern CI/CD practices.

- Integrate advanced AI models (LLMs/VLMs, world models) into robotics workflows for perception and decision-making.

- Collaborate with cross-functional global teams and support client workshops, demos, and solution documentation.

- Drive technical execution for POCs, pilots, and scalable robotics deployments.

Must Have:

- 13+ years of overall industry experience with 6+ years of core robotics experience.

- Bachelor's or Master's degree in Robotics, Mechatronics, Computer Science, or a related engineering field.

- Proven expertise as a ROS/ROS2 Architect - designing, building, and scaling modular robotics software stacks.

- Strong proficiency in Python, C++, ROS2, and robotics middleware.

- Deep understanding of robot kinematics, dynamics, motion planning, SLAM, and control algorithms.

- Hands-on experience with simulation tools such as Isaac Sim, NVIDIA Omniverse, Gazebo, Webots, or MuJoCo.

- Proven experience in AI/ML for robotics (Computer Vision, Deep Learning, Reinforcement Learning) and deploying models on embedded systems.

- Strong applied knowledge of LiDAR, depth cameras, stereo vision, IMUs, and sensor fusion methodologies.

- Experience in Navigation & Autonomy: path planning, SLAM, obstacle avoidance, and autonomous mobile systems.

- Experience in Manipulation: trajectory planning, end-effector control, and collaborative robot (cobot) integration.