Amazon's Frontier AI & Robotics (FAR) team is seeking a Member of Technical Staff to drive foundational research and build intelligent robotic systems from the ground up. In this role, you will operate at the intersection of innovative AI research and real-world robotics - conducting original research, publishing, and deploying your innovations into production systems at Amazon scale. We're looking for researchers who think from first principles, push the boundaries of what's possible, and take full ownership of turning breakthrough ideas into working systems.
You will join the next revolution in robotics, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As a Member of Technical Staff, you'll develop breakthrough foundation models that enable robots to perceive, understand, and interact with the physical world in unprecedented ways-with a strong emphasis on the hardware systems that bring these models to life. You'll drive independent research initiatives in areas such as locomotion, manipulation, motor control, actuator design, sim2real transfer, and multi-modal robot learning, designing novel frameworks that bridge state-of-the-art research with real-world hardware deployment at Amazon scale.
In this role, you'll balance innovative technical exploration with hands-on hardware implementation, collaborating with mechanical, electrical, and controls engineering teams to ensure your models and algorithms perform robustly on physical robotic platforms in dynamic real-world environments. You'll have access to Amazon's computational resources and advanced robotics infrastructure-including high degree-of-freedom prototype platforms, custom actuators, and precision sensing systems-enabling you to tackle ambitious problems in areas like multi-modal robotic foundation models, motor-level control optimization, and efficient model architectures that scale across diverse robotic hardware.
Key job responsibilities
- Drive independent research initiatives across the full robotics stack, including robot co-design, manipulation mechanisms, innovative actuation and motor control strategies, state estimation, low-level control, system identification, reinforcement learning, and sim-to-real transfer, as well as foundation models for perception and manipulation
- Lead full-stack robotics projects from conceptualization through hardware deployment, taking a system-level approach that integrates actuator dynamics, sensor feedback (force/torque, IMUs, encoders), and electromechanical constraints with algorithmic development
- Develop and optimize control algorithms and sensing pipelines for physical robotic hardware, including motor characterization, actuator performance tuning, and robust sensor integration in production environments
- Collaborate with hardware, mechanical, and electrical engineering teams to ensure seamless integration of learned models across the robotics stack-from embedded compute and communication buses to actuator-level control
- Contribute to the team's technical strategy and help shape our approach to next-generation hardware-aware robotics challenges, including hardware-in-the-loop validation and prototype-to-deployment transitions
A day in the life
- Design and implement innovative systems and algorithms, leveraging our extensive computational and robotics hardware infrastructure to prototype and evaluate at scale
- Collaborate with hardware and software engineers to solve complex technical challenges spanning motors, actuators, sensors, and learned control
- Lead technical initiatives from conception to hardware deployment, working closely with robotics engineers and lab teams to integrate your solutions into physical robotic platforms
- Participate in technical discussions and design reviews with team leaders, hardware engineers, and fellow scientists
- Leverage our compute cluster and advanced robotics lab-including high-DoF prototype platforms and custom actuation systems-to rapidly prototype and validate new ideas
- Transform theoretical insights into practical solutions that perform reliably on real-world robotic hardware
Amazon.com · San Francisco, CA