Robotics Engineer: Manipulation Systems and Deployment

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

• 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.

Minimum Qualifications

• 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.

Bonus Qualifications

• 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.

Desired Start Date

7/6/2026

Position Keywords

Robotics, Systems, Manipulation, Machine Learning, Controls

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