Senior Applied Scientist, Navigation

Amazon • San Francisco, CA

6d • Onsite

About The Position

Amazon is redefining the future of automation with advanced robotic systems that integrate AI, control systems, and mechanical design for adaptable, intelligent automation solutions. These systems operate safely alongside humans in dynamic, real-world environments. The company leverages machine learning, artificial intelligence, and advanced robotics to solve complex operational challenges at a global scale, with a fleet of robots in hundreds of facilities worldwide. The Sr. Scientist in Robot Navigation will be instrumental in architecting and delivering intelligent, safe, and scalable navigation systems. This role requires deep expertise in learning-based planning and control, a strong understanding of foundation models for embodied agents, and in-depth knowledge of control-theoretic approaches like Model Predictive Control (MPC) for trajectory planning. The goal is to develop navigation solutions that combine data-driven intelligence with principled control-theoretic guarantees, enabling robots to move fluidly and safely through dynamic environments by understanding context, anticipating change, and adapting in real-time. The role involves leading research that bridges academic advances with production-grade deployment, collaborating with teams focused on robotic autonomy, manipulation, and human-robot interaction.

Requirements

• Experience programming in Java, C++, Python or related language
• Have publications at top-tier peer-reviewed conferences or journals
• PhD in Robotics, Computer Science, Electrical Engineering, Controls, or a related field
• 5+ 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)

Nice To Haves

• 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-languageaction 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

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 including robotics engineers, software engineers, and product managers to define and deliver perception capabilities
• Drive end-to-end ownership of ML models — from data collection and labeling strategy 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 their limitations post-deployment
• Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations
• Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team
• Mentor team members while maintaining significant hands-on contribution to technical solutions

Benefits

• sign-on payments
• restricted stock units (RSUs)
• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree