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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Applied Scientist, Navigation - **Company:** Amazon.com, Inc. - **Location:** Sunnyvale, CA, United States - **Experience:** Expert - **Salary:** $192,200.0 - $260,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Computer Vision, C++ (Programming Language), Middleware, Formal Verification, Python (Programming Language), Machine Learning, Motion Planning, Object Detection, Sensor Fusion, Reinforcement Learning, Pytorch, Multi-Agent Systems, Safety Critical Systems, Information Technology - **Published:** August 7, 2026 - **Apply:** https://www.jobmonkeyjobs.com/career/27912883/Senior-Applied-Scientist-Navigation-California-Sunnyvale-7375 ## About the Role 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) - Proven track record of translating research into deployed systems, 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 ## Description 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 A day in the life - 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 About the team Our team is a group is a diverse group of scientists and engineers passionate about building intelligent machines. 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