Hiring: Sr. Applied Scientist, Fauna Company: Amazon Location: Sunnyvale, CA Job Posted Time: 2026-09-09 17:58:26 Employment Type: Full-time Target Skills & Keywords: Robot Navigation, Autonomous Systems, Sim-to-Real Transfer, Classical Navigation, Learning-Based Navigation, Foundation Models, Spatial Reasoning, Simulation & Benchmarking, Python, C++, Robotics, Machine Learning, AI Experience: - PhD, or Master's degree and 6+ years of applied research experience - 3+ years of industry or academic research experience - Demonstrated track record of leading technical projects - Experience mentoring junior scientists/engineers Required Skills: - Strong publication record at major Robotics/ML/AI conferences (e.g., RSS, CoRL, ICRA, IROS, NeurIPS, ICML, ICLR) - Programming in Python, C++, or related language - Experience with sim-to-real transfer for robotic systems - Developing robust navigation systems for complex, dynamic indoor environments with static and dynamic obstacles - Building simulation-based and on-device evaluation frameworks with benchmarks and metrics - Conducting sim-to-real transfer experiments and analyzing performance gaps - Collaborating with cross-functional teams (world model, manipulation) for system integration - Staying current with advances in robot navigation and spatial reasoning Qualifications: - PhD, or Master's degree and 6+ years of applied research experience - 3+ years of industry or academic research experience - Strong publication record at major Robotics/ML/AI conferences - Experience programming in Python, C++, or related language - Experience with sim-to-real transfer for robotic systems - Demonstrated track record of leading technical projects - Experience mentoring junior scientists/engineers - Preferred: History of impactful first-author publications at major conferences - Preferred: Experience bridging research with practical engineering implementation in robotics systems - Preferred: Experience with visual navigation, semantic navigation, or foundation models applied to robot navigation - Preferred: Experience evaluating and benchmarking multiple navigation approaches (classical, learning-based, foundation model-based) Compensation: Not specified Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don’t miss this opportunity to join a forward-thinking team!