Applied Scientist, Navigation
About the role
Amazon is building the next generation of advanced robotic systems that blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments. As a Scientist in Robot Navigation, you will architect and deliver navigation systems that are intelligent, safe, and scalable, combining data-driven intelligence with control-theoretic guarantees. You will lead research bridging academic advances and production-grade deployment, collaborating with world-class teams in robotic autonomy, manipulation, and human-robot interaction.
Responsibilities
- Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding.
- Lead research initiatives in computer vision, sensor fusion, and 3D perception.
- Collaborate with cross-functional teams (robotics engineers, software engineers, product managers) to define and deliver perception capabilities.
- Drive end-to-end ownership of ML models—from data collection and labeling to training, evaluation, and deployment.
- Mentor junior scientists and engineers; contribute to a culture of technical excellence.
- Define and track key metrics to measure perception system performance in real-world environments.
- Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents.
- Train ML models for deployment in simulation and real-world robots; identify and document limitations post-deployment.
- Drive technical discussions and brainstorming sessions to develop innovative solutions.
- Maintain significant hands-on contribution to technical solutions while mentoring team members.
Requirements
- PhD in Robotics, Computer Science, Electrical Engineering, Controls, or a related field.
- 2+ years of experience in robot navigation, motion planning, or autonomous systems.
- Deep expertise in learning-based approaches to navigation (e.g., imitation learning, reinforcement learning, neural motion planning, diffusion-based policies).
- Strong experience with Model Predictive Control (MPC) and optimization-based planning (PyTorch, JAX, or equivalent).
- Proven track record of translating research into deployed systems.
- Experience programming in Java, C++, Python, or a related language.
Preferred Qualifications
- Experience applying foundation models or large pre-trained models to robotics tasks (navigation, manipulation, or embodied AI).
- Familiarity with world models, visual navigation, or vision-language-action models.
- Experience with sim-to-real transfer and high-fidelity simulation environments (Isaac Sim, MuJoCo, Gazebo).
- Knowledge of SLAM, localization, and mapping systems.
- Experience with ROS/ROS2 and real-time robotics middleware.
- Hands-on experience deploying navigation systems on physical robots in dynamic, real-world environments.
- Experience with safety-critical systems and formal verification of learned controllers.
- Familiarity with multi-agent coordination and fleet-level navigation.
About the team
Our team is a diverse group of scientists and engineers passionate about building intelligent machines. We value curiosity, rigor, and a bias for action, believing in learning from failure and iterating quickly toward solutions that matter.
Pay
- USA, CA, San Francisco: $171,600.00 - $222,200.00 USD annually
- USA, CA, Sunnyvale: $171,600.00 - $222,200.00 USD annually
- USA, MA, North Reading: $142,800.00 - $193,200.00 USD annually
Benefits
- Comprehensive health insurance (medical, dental, vision, prescription, Basic Life & AD&D, and optional supplemental life plans).
- Employee Assistance Program (EAP), Mental Health Support, and Medical Advice Line.
- Flexible Spending Accounts.
- Adoption and Surrogacy Reimbursement coverage.
- 401(k) matching.
- Paid time off and parental leave.
- Sign-on payments and restricted stock units (RSUs).