Director of Science, Geospatial

Amazon Amazon · Big Tech · Bellevue, WA · Machine Learning Science

Director of Science, Geospatial at Amazon, leading a team of ~50 scientists focused on AI/ML solutions for last-mile delivery operations. The role involves developing and deploying solutions for geospatial problems, including address validation, place datasets, road networks, and leveraging edge data. Key focus areas include GenAI (LLMs, VLMs, agents), computer vision, and traditional ML to optimize delivery routes, improve data fidelity, and drive business impact. The role requires interfacing with senior stakeholders, strategic planning, and building a high-performing team.

What you'd actually do

  1. Lead a worldwide team of scientists to develop and deploy AI and ML solutions for geospatial problems to accelerate and optimize Amazon's global delivery operations
  2. Interface with senior stakeholders across engineering, product, and operations teams to design end-to-end solutions, execute model delivery to production, and drive shared goals
  3. Contribute to strategic planning by developing yearly and 3-year planning documents
  4. Present to senior executives (VPs) and stakeholders via demo sessions, science reports, and quarterly business reports
  5. Drive innovation by leveraging SOTA scientific techniques ranging from GenAI (LLMs/VLMs/agents), computer vision, and traditional ML to solve delivery-related problems

Skills

Required

  • MS in a quantitative field (CS, Math, Statistics, OR, Engineering etc.)
  • 10+ years experience leading applied science and engineering teams in an industrial setting
  • Proven experience of delivery of multiple science-based solutions to production with business impact
  • Experience building and managing specialized teams

Nice to have

  • expertise in generative AI, computer vision, and machine learning
  • broad and deep skills in innovative AI and ML techniques
  • experience with LLMs, VLMs, agentic paradigms, and reasoning agents
  • experience with scaled inputs like satellite, aerial, and camera imagery
  • experience with multi-modal workflows and solvers

What the JD emphasized

  • Proven experience of delivery of multiple science-based solutions to production with business impact
  • Experience building and managing specialized teams

Other signals

  • leading a worldwide team of scientists
  • developing and deploying AI and ML solutions
  • accelerating and optimizing global delivery operations
  • leveraging SOTA scientific techniques ranging from GenAI (LLMs/VLMs/agents), computer vision, and traditional ML
  • building and managing specialized teams