Applied Science Manager, Prime Air

Amazon

San Francisco (CA)

On-site

USD 183,800 - 248,700

Full time

14 days+

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Benefits offered by this job

Health insurance
401(k) matching
Paid time off
Parental leave

Job summary

A leading technology company in San Francisco seeks an Applied Science Manager to enhance its drone delivery system. You will lead a talented team of scientists and engineers, focusing on improving delivery rates through advanced machine learning and geospatial data analytics. Ideal candidates should possess a PhD or Master’s in relevant fields and demonstrate expertise in path planning and optimization strategies. The role offers a competitive salary and comprehensive benefits.

Qualifications

  • Experience managing a team in a production environment.
  • Strong foundation in geospatial data analysis.
  • Proven track record of applying reinforcement learning to optimization problems.

Responsibilities

  • Lead and mentor a team of Applied Scientists and Engineers.
  • Leverage ML/RL to develop dynamic path-planning algorithms.
  • Drive development of high-scale scheduling systems.
  • Utilize deep geospatial data to improve mission safety.

Skills

Leadership
Machine Learning
Geospatial Information Systems
Path Planning

Education

PhD or Master’s degree in Computer Science, Robotics, Operations Research, or related field

Tools

Machine Learning Models
GIS Software

Job description

Job ID: 10397305 | Amazon.com Services LLC

Overview

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.

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 is 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 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.
  • 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.
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 (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.
  • Experience communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs.
  • Experience hiring and growing top talent.
  • Knowledge of engineering practices and patterns for the full software/hardware/network development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations.
  • Ability to turn ambiguous "blue‑sky" research into deployed, high‑impact features.
Benefits and Compensation

Base salary range: 183,800.00 – 248,700.00 USD annually (USA, WA, Seattle). Your Amazon package will include sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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