The Challenge
How do you orchestrate a fleet of autonomous drones to deliver packages safely in under an hour, while maximizing every minute of flight time? How do you scale a mission planning system to handle thousands of concurrent deliveries in complex, shifting environments?
Our team of scientists, engineers, and aerospace professionals is solving these exact problems. We are looking for an Applied Science Manager to lead the evolution of our Mission Planning and Orchestration System. You will be at the forefront of defining how Prime Air moves from point A to point B with maximum efficiency.
The Role
As an Applied Science Manager, you will lead a high-caliber team of scientists and engineers focused on the "brains" of our fleet orchestration. You will bridge the gap between Geospatial Intelligence and Machine Learning to revolutionize our path planning and scheduling algorithms. Your primary north star? Increasing deliveries per hour (DPH) through intelligent, automated optimization.
Key Responsibilities:
Lead & Mentor: Manage a cross-functional team of Applied Scientists and Engineers, fostering a culture of scientific rigor and rapid iteration.
Innovate Path Planning: Leverage ML/RL and heuristic search techniques to develop dynamic path-planning algorithms that navigate complex airspace and weather patterns.
Optimize Orchestration: Drive the development of high-scale scheduling systems that manage battery life, maintenance cycles, and delivery windows to maximize fleet utilization.
Geospatial Mastery: Utilize deep geospatial data (3D maps, urban topology, etc.) to improve situational awareness and mission safety.
System Architecture: Define the long-term technical roadmap for mission orchestration, ensuring our systems are modular, scalable, and resilient.
Cross-Functional Collaboration: Partner with Hardware, Flight Safety, and Supply Chain teams to translate business requirements into technical breakthroughs.
Basic Qualifications
Experience managing a team of scientists and/or engineers in a production environment.
PhD or Master's degree in Computer Science, Robotics, Operations Research, or a related field.
Strong foundation in Geospatial Information Systems (GIS) and spatial data analysis.
Proven track record of applying Machine Learning (e.g., Reinforcement Learning, Graph Neural Networks) to optimization problems like path planning or vehicle routing.
Preferred Qualifications
Experience with autonomous systems, UAVs, or large-scale logistics networks.
Knowledge of combinatorial optimization and real-time scheduling constraints.
A knack for turning ambiguous "blue sky" research into deployed, high-impact features.
Export Control License: This position may require a deemed export control license for compliance with applicable laws and regulations. Placement is contingent on Amazon's ability to apply for and obtain an export control license on your behalf.
Key job responsibilities
Strategic Technical Leadership & Throughput: Lead the development of path planning and geospatial orchestration models to maximize deliveries per hour, ensuring complex algorithms are production-ready and integrated into the mission system.
Team Management & Delivery: Build and scale a world-class science team by mentoring talent and fostering career growth, while maintaining a high bar for operational excellence to deliver mission-critical software on schedule.
A day in the life
In a typical day, you lead an agile squad through high-velocity sprints, starting with a stand-up to unblock path-planning prototypes and ensure the team is on track for mission-critical delivery milestones. You spend your time bridging the gap between research and reality, reviewing code and design docs to ensurealgorithms for geospatial orchestration are production-ready and optimized for real-world drone throughput. Between deep-dive technical reviews, you focus heavily on people development-conducting 1:1s to mentor scientists and architecting career growth paths-while collaborating with cross-functional leads to ensure your team"s innovations seamlessly integrate into the live mission planning system.
About the team
We"re a mix of software developers, applied and research scientists, and geospatial experts as well as system developers.