We are hiring for one of our clients, seeking a Member of Technical Staff, Robotics Research to advance autonomous navigation systems for industrial robotic platforms, driving algorithmic improvements in sensor fusion and real-time decision-making frameworks, fully remote.
 About the Role — Autonomous Robotics Research
Core Scope: Advancing autonomous navigation systems for industrial robotic platforms
Technical Focus: Sensor fusion, real-time decision-making, and perception algorithms
Compensation: $500K – $1,500K/yr
Work Format: Fully remote, work from anywhere
Core Frameworks: ROS/ROS2, Gazebo, and similar simulation environments
 Career Impact & Robotics Research Opportunity
Total Flexibility: Fully remote role, work from anywhere globally
Technical Ownership: Design perception algorithms and optimize path planning systems
Research Impact: Publish findings in peer-reviewed conferences and journals
Career Growth: Access to cutting-edge hardware and computational resources for research
Position Overview
The role involves advancing autonomous navigation systems for industrial robotic platforms. Candidates will drive algorithmic improvements in sensor fusion and real-time decision-making frameworks, contributing to the development of next-generation robotic systems with access to cutting-edge hardware and computational resources.
 Why This Role Matters: As Member of Technical Staff, Robotics Research, you design and implement perception algorithms for multi-modal sensor integration in dynamic environments, develop and optimize path planning and motion control systems for robotic manipulators and mobile platforms, lead experimental validation of robotic systems in both simulation and real-world deployments, collaborate with cross-functional teams to integrate research prototypes into production-grade systems, and publish findings in peer-reviewed conferences and journals, advancing the state of the art in autonomous robotics while working with a global technology leader.
 Key Responsibilities
Perception & Sensor Integration
- Design and implement perception algorithms for multi-modal sensor integration in dynamic environments
Motion Planning & Control
- Develop and optimize path planning and motion control systems for robotic manipulators and mobile platforms
Experimental Validation
- Lead experimental validation of robotic systems in simulation and real-world deployments
Cross-Functional Integration & Publication
- Collaborate with cross-functional teams to integrate research prototypes into production-grade systems
- Publish findings in peer-reviewed conferences and journals to advance the state of the art
 Qualifications & Requirements
Educational Requirements
- PhD or Master’s degree in Robotics, Computer Science, Electrical Engineering, or related field
Experience Requirements
- 5+ years of hands-on experience in robotics research with a focus on autonomy or manipulation
- Strong background in SLAM, sensor fusion, or reinforcement learning for robotic applications
Essential Skills
- Proficiency in C++ and Python for algorithm development and system integration
- Experience with ROS/ROS2, Gazebo, or similar simulation and development frameworks
About the Opportunity
This role offers a unique opportunity to work with a global leader in the Technology, Information and Internet industry, contributing to the development of next-generation robotic systems. The position provides access to cutting-edge hardware and computational resources for research, hiring is conducted by a staffing partner on behalf of the end client, and all qualified candidates are welcome regardless of background, experience, or prior employment history.
Career Excellence: Advance the state of the art in autonomous robotics research with a global technology leader, in a fully remote role offering elite-tier compensation and cutting-edge research resources.
 Who Should Apply?
- PhD/Master’s Robotics Researchers:Â With 5+ years focused on autonomy or manipulation
- SLAM & Sensor Fusion Specialists:Â Experienced in multi-modal sensor integration
- Reinforcement Learning Engineers:Â Applying RL to robotic applications
- ROS/ROS2 Developers:Â Proficient with Gazebo and simulation-based development
- Remote-First Research Scientists:Â Comfortable publishing in peer-reviewed venues while working remotely
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