Amazon's Last Mile Delivery organization is responsible for the on-time and error-free delivery of tens of billions of packages annually, in 20+ countries worldwide. The organization's focus over the years has expanded beyond package delivery to include groceries and heavy and bulky items and has dramatically increased the speed of delivery from two day, to one day, to sub-same day for millions of items, a trend that will continue with quick commerce deliveries within minutes. Underpinning this massive delivery logistics operation (one of the largest in the world) is innovative technology leveraging state of the art AI and ML solutions developed by the Geospatial Science team, one of the largest science teams within the Amazon Operations organization. The Geospatial Science team is responsible for the quality and coverage of the core geospatial data, solvers, and real-time workflows that operate over petabytes of data, power trillions of transit time calculations daily, and operate on diverse environments spanning multi-modal cloud-based learning workflows, highly throughput and low-latency services, and edge compute applications on smart phones, delivery vehicles, and delivery stations. Geospatial Science capabilities operate at the critical path a broad array of mission critical workflows ranging from customer address creation, order placement, delivery route planning, delivery route execution, and package drop-off.
The Director, Applied Science (Geospatial) owns the end-to-end science portfolio that enables these capabilities by leveraging innovative AI and ML techniques. They are responsible for (1) learning and improving a worldwide catalog of addresses with high-quality validation and geo-resolution, (2) building a places dataset to model where we delivery ranging from every single single-family home, campus, building, and apartment - along with their relationships and delivery critical attributes such as delivery hours, access information, mail rooms, delivery lockers, parking locations, entrances, and drop-off geocodes, (3) developing maps that capture a fresh and accurate road network, enable precise transit paths that optimize travel times while reducing travel risk in delivery routes and on-road navigation experiences and (4) developing feedback loops that leverage edge capabilities of millions of smart phones and tens of thousands of delivery vehicles to capture fresh street imagery, learn street signs, road markings, and road obstructions at scale, and reconstruct key delivery events and activities to improve the fidelity of address, place, and road datasets, optimize routes, and reduce defects.
This leader will lead a worldwide team of approximately 50 scientists, with expertise in generative AI, computer vision, and machine learning. This leader requires broad and deep skills in innovative AI and ML techniques to take advantage of the latest advances in the field. A key focus is accelerating the development and adoption of GenAI-based solutions, in the face of rapid shifts in the science and technology landscape, by guiding the team to maximize the value that can be delivered using latest LLMs, VLMs, agentic paradigms, and reasoning agents. Computer vision based solutions form an important part of the portfolio, as the team innovates on scaled inputs like satellite, aerial, and camera imagery for many problems, such as road learning and transporter safety. This leader will be expected to invest in research and innovation to deliver novel solutions to unlock new opportunities to grow the business while making pragmatic tradeoffs to deliver timely customer value, in conjunction with product, engineering, and operational leaders and teams.
This leader will be expected to interface with senior leaders (up to SVP) and senior partners and stakeholders across the World-Wide Operations organization and Amazon. Day-to-day interactions will span product partners with whom s/he will design end-to-end customer solutions and long-term product plans and strategies, engineering partners with whom s/he will execute the development and productization of multi-modal workflows and solvers, and multi-disciplinary upstream and downstream stakeholders and partner teams. This leader will be expected to co-own yearly and 3-year planning documents for the Geospatial Technology space. S/he will also be expected to build and demonstrate advanced research prototypes and proposals up to the SVP level. S/he will be expected to recruit senior scientists and science leaders and managers for their own team as well as other peer teams across Amazon. S/he will need build and maintain a high-performing team and develop and promote scientists and science leaders (up to Principal/Sr Manager/Sr Principal).
Key job responsibilities