Applied Scientist II, Amazon Fulfillment Technology , Amazon Fulfillment Technologies (AFT)

We are the Amazon Fulfillment Technologies (AFT) Science team. We design, build, and deploy optimization, simulation, and machine learning solutions that power the production systems running in Amazon’s global Fulfillment Centers. Our work spans labor planning and staffing, demand prioritization, pick assignment and scheduling, and flow-process optimization. We create innovative, scalable, and reliable science-driven solutions that run continuously at massive scale—often every few minutes to hours per use case—and push beyond the published state of the art.

About the team

The AFT Science team combines expertise in operations research, optimization, scheduling, planning, simulation, and machine learning with deep domain knowledge of fulfillment-center processes and their pain points. We prioritize advancements that support AFT technology teams and focus areas rather than specific research fields or individual business partners. Our influence spans the entire innovation lifecycle, from inception to deployment, whether we are developing novel solutions or improving existing ones. Production systems we build rely on a diverse technology stack, so our teams invest in multiple specialties as each focus area evolves.

Responsibilities

• Develop domain knowledge of operational processes, system architecture, and business requirements.
• Deep-dive into data and code to identify opportunities for continuous improvement or disruptive new approaches.
• Develop scalable mathematical models for production systems to derive optimal or near-optimal solutions for existing and new challenges.
• Create prototypes and simulations for agile experimentation of devised solutions.
• Advocate technical solutions to business stakeholders, engineering teams, and senior leadership.
• Partner with engineers to integrate prototypes into production systems.
• Design experiments to test new or incremental solutions launched in production and build metrics to track performance.

Requirements

• PhD, or Master’s degree and 4+ years of experience in a science, technology, engineering, or related field.
• 2+ years of experience building models for business applications.
• Experience programming in Java, C++, Python, or a related language.
• Relevant industry or academic applied research experience in operations research, optimization, machine learning, statistics, or an equivalent field.

Preferred Qualifications

• PhD with applied research experience and expertise in Operations Research, Optimization, Machine Learning, Statistics, or an equivalent field.
• Experience with large-scale optimization and decomposition techniques, planning, and scheduling problems.
• Experience building machine learning models and developing algorithms for business applications.
• Experience developing and deploying code for production systems.
• Experience with exploratory data analysis and experimental design.

Benefits

• Medical, dental, and vision coverage.
• Maternity and parental leave options.
• Paid time off (PTO).
• 401(k) plan with company matching.
• Sign-on payments and restricted stock units (RSUs).
• Basic Life & AD&D insurance and optional supplemental life plans.
• Employee Assistance Program (EAP) and mental health support.
• Medical Advice Line.
• Flexible Spending Accounts.
• Adoption and surrogacy reimbursement coverage.

Pay

Base salary range: $142,800 – $193,200 USD annually (Bellevue, WA). Final compensation will be determined based on experience, qualifications, and location.