Robotics Research Engineer, Reality Labs Research

We are seeking a Research Engineer with expertise in software engineering, robotic systems integration, and machine learning to join Reality Labs Research. This role is highly interdisciplinary, involving full-stack development, deployment of control policies, and hands-on work with robotic embodiments and human wearable sensing systems. You'll collaborate with researchers, engineers, and designers, leveraging cutting-edge technology and facilities.

Robotics Research Engineer, Reality Labs Research Responsibilities:

• Architect Data Capture Systems: Integrate motion capture and novel hardware prototypes for human demonstration data
• Design Data Processing Pipelines: Build scalable pipelines for large multimodal datasets to enable efficient model training
• Orchestrate Robotic Systems: Develop and maintain real-time orchestration pipelines, integrating multidisciplinary components
• Optimize and Debug: Tune runtime performance, debug system behavior, and develop interactive demos and benchmarks
• Collaborate Cross-Functionally: Work with interdisciplinary teams to refine modules and drive end-to-end system improvements

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 5+ years of research or industry experience in perception, machine learning, or robotics
• 3+ years of full-stack systems engineering experience, including large software systems development and maintenance
• Experience with prototype/scientific software-hardware systems (robotics platforms, multi-camera systems, human sensing systems)
• Track record of collaborating and communicating effectively across functions

• Master's or Ph.D. in Robotics, Computer Science, Electrical Engineering, or related field (or equivalent practical experience)
• Experience in robotics research, especially dexterous manipulation, robotic policy, and control theory
• Familiarity with robotics frameworks (e.g., ROS) and real-world robotic control systems
• Experience designing data collection protocols, developing data pipelines, and building high-quality ML datasets
• Background in computer vision, imitation learning, reinforcement learning, self-supervised learning, model-predictive control, or other advanced ML/CV techniques