What are the responsibilities and job description for the Robotics Engineer: Manipulation Systems and Deployment ... position at Honda Research Institute USA, Inc.?
Job Number: P25F02
Honda Research Institute USA (HRI-US) is seeking a highly motivated Robotics Engineer to join our Intelligent Robotics Research Division to develop and deploy robotic manipulation systems using Honda’s proprietary hardware platforms, with a focus on bringing advanced manipulation algorithms on real robotic systems. The role requires a strong foundation in both modern machine learning techniques and robotics control. The ideal candidate will have experience implementing robotics algorithms on real-world systems, integrating perception, planning, and control modules, and deploying learning-based or control-based manipulation methods on real robotic hardware. They will bridge the gap between research and real-world deployment by understanding state-of-the-art machine learning approaches and control strategies, and translating them into robust, scalable robotic solutions. This position plays a key role in enabling application-oriented robotics and accelerating the deployment of intelligent manipulation systems in real-world environments.
San Jose, CA
Key Responsibilities
Honda Research Institute USA (HRI-US) is seeking a highly motivated Robotics Engineer to join our Intelligent Robotics Research Division to develop and deploy robotic manipulation systems using Honda’s proprietary hardware platforms, with a focus on bringing advanced manipulation algorithms on real robotic systems. The role requires a strong foundation in both modern machine learning techniques and robotics control. The ideal candidate will have experience implementing robotics algorithms on real-world systems, integrating perception, planning, and control modules, and deploying learning-based or control-based manipulation methods on real robotic hardware. They will bridge the gap between research and real-world deployment by understanding state-of-the-art machine learning approaches and control strategies, and translating them into robust, scalable robotic solutions. This position plays a key role in enabling application-oriented robotics and accelerating the deployment of intelligent manipulation systems in real-world environments.
San Jose, CA
Key Responsibilities
- Develop and deploy integrated robotic manipulation algorithms (perception, planning, control, learning) on Honda's proprietary hardware, with a focus on robustness and real-world performance.
- Debug, evaluate, and optimize robotic manipulation algorithms through experimentation, testing, and failure analysis.
- Implement and adapt algorithms from research papers (e.g., reinforcement learning, imitation learning, vision-based policies) into practical, deployable solutions.
- Apply knowledge of robotics control (e.g., kinematics, dynamics, motion control, force/impedance control) together with machine learning to improve manipulation performance.
- Support sim-to-real validation using simulation tools.
- Document and support system demos and cross-team development.
- Collaborate with Honda’s global research organizations to align system development, share technical insights, and co-develop robotics capabilities.
- M.S. in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field.
- Strong experience with real robotic systems development and deployment.
- Solid background in robotics control and machine learning for robotics.
- Proficiency in Python and/or C , and ROS/ROS2.
- Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
- Familiarity with simulation tools (e.g., Isaac Sim, MuJoCo)
- Experience integrating full robotic pipelines and debugging real systems.
- 2 years of experience with dexterous manipulation, multi-fingered robotic hands, or contact-rich manipulation tasks.
- Hands-on experience deploying learning-based manipulation policies on real robots.
- Strong experience with simulation environments and sim-to-real pipelines.
- Experience with domain adaptation, system identification, or techniques to reduce sim-to-real gaps.
- Familiarity with tactile sensing, force/torque sensing, or compliant control.
- Experience working with vision-language models (VLMs) or other foundation models for robotics.
- Experience working with custom or proprietary robotic hardware systems.
- Experience working with teleoperation and human-in-the-loop workflows, including interfacing with devices such as gloves or VR systems for control, data collection, and evaluation.
- Track record of improving robustness and reliability of robotic systems in real environments.