Sr. Applied Scientist, Amazon Robotics, Structured Field Coordinated Planning & Control

Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet.

We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun.

• Lead research initiatives advancing AI-driven structured field robotics (path planning, fleet coordination, control systems) and translate breakthroughs into production solutions at global scale
• Own end-to-end delivery of complex algorithmic solutions from design through production deployment and operational maintenance
• Drive technical decisions for Control, Coordination, and Path Planning systems meeting performance, scalability, and reliability requirements
• Partner with cross-functional teams to translate business requirements into research problems and assess technical risks
• Influence technical direction across the broader robotics organization through design reviews and technical discussions with senior engineers and scientists
• Demonstrate measurable impact through AI-driven algorithmic improvements: fleet efficiency gains, operational cost reduction, system reliability improvements, and enhanced customer experience
• Publish findings at top-tier AI and robotics conferences representing organizational technical leadership
• Mentor junior Applied Scientists on research methodology and balancing innovation with production constraints
• Operate independently on ambiguous, multi-quarter problems requiring novel AI approaches while navigating tradeoffs between research innovation and production constraints

Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.

• Medical, Dental, and Vision Coverage
• Maternity and Parental Leave Options
• Paid Time Off (PTO)
• 401(k) Plan

If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!

At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

We're the structured field robotics organization powering large-scale mobile robotics operations globally. Our mission is to enable safe, efficient, and reliable robotic operations through intelligent Control, Coordination, and Path Planning systems.

We operate at the intersection of planning, algorithmic, and ML research with production systems, owning the full stack from innovation to deployment.

Our culture balances research excellence with operational ownership. Applied Scientists partner closely with engineers: reviewing code, contributing to research discussions, and solving problems together. We value deep technical expertise alongside pragmatic engineering judgment. We invest in our people through mentorship and encourage conference participation and knowledge sharing.

• PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 5+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with conducting research in a corporate setting
• 3+ years of industry or academic research experience
• 3+ years of building machine learning models or developing algorithms for business application experience
• Have publications on top-tier conferences, such as CVPR, ICCV, ECCV or NeurIPS
• Strong foundation in motion planning algorithms (A*, RRT, optimization-based planning) and…