Role & Responsibilities / What youll do:
The candidate will lead the design, development, and integration of robotics applications that combine perception, AI inference, motion planning, manipulation, navigation, and real-time robot control.
The role involves developing end-to-end robotics software applications for humanoid robots, robotic manipulators, AMRs, and other intelligent autonomous systems. The candidate will work closely with hardware, embedded systems, AI/ML, and product engineering teams to transform AI capabilities into reliable, deployable robotic products.
The ideal candidate has to have hands-on experience developing ROS 2 applications, integrating open-source robotics frameworks and AI models, and deploying software on embedded compute platforms.
- ROS 2 Application Development
- Physical AI Application Development
- Robot Hardware and Sensor Integration
- Edge AI and Deployment
- Simulation, Testing, and Validation
Required skills / Whom we are looking for:
- Experience with humanoid robots, AMRs, robotic arms, quadrupeds, or autonomous systems.
- Experience with NVIDIA Isaac ROS, Isaac Sim, Isaac Lab, or related robotics tools.
- Experience delivering customer-facing demonstrations or commercial robotics products.
Programming and software engineering
- Strong C++ and Python programming skills.
- Object-oriented design, software architecture, debugging, profiling, and performance optimization.
- Linux development, Git, CMake, GDB, and build/debug workflows.
ROS 2
- Hands-on experience developing production-oriented ROS 2 applications.
- Strong understanding of ROS 2 communication, executors, QoS, DDS, TF2, launch systems, and custom interfaces.
- Experience integrating third-party ROS 2 packages and debugging multi-node systems.
Robotics
- Understanding of robot kinematics, coordinate frames, trajectories, navigation, and manipulation.
- Practical experience with at least one of Nav2, MoveIt 2, ros2_control, SLAM, and robot SDK integration.
- Familiarity with robot simulation and real-world deployment.
- Experience integrating AI/ML models into robotics applications.
- Familiarity with computer vision, object detection, tracking, segmentation, pose estimation, or multimodal AI.
- Understanding of AI inference pipelines and deployment on edge compute hardware.
- Performance analysis, documentation, version control, and collaborative software development.
Nice-to-haves
- Experience with BSP development and board bring-up.
- Familiarity with VLM/VLA models, imitation learning, behavior trees, and task planning.
- Real-time control integration, embedded Linux, sensor drivers, and hardware interfaces.
- Contributions to open-source robotics projects or reusable robotics software frameworks.
- Experience with WebRTC, voice interfaces, multimodal interaction, or remote robot monitoring.
- AI/ML model development/optimization for Edge applications on DSP/NPU/GPU