Does the thought of improving one of the world’s most complex logistic systems inspire you? Is your passion to sift through hundreds of systems, processes, and data sources to solve the puzzle and identify the next big opportunity? Are you a creative big thinker who is passionate about using data to direct decision making and solve complex and large-scale challenges? Are you fascinated by the interactions between operations and strategy? Do you feel like your skills uniquely qualify you to bridge communication between teams with competing priorities? If so, then this position is for you!

Come help Amazon create cutting-edge science-driven technologies for delivering packages to the doorstep of our customers! The Last Mile Routing & Planning organization builds the software, algorithms and tools that make the “magic” of home delivery happen: our flow, sort, dispatch and routing intelligence systems are responsible for the billions of daily decisions needed to plan and execute safe, efficient and frustration-free routes for drivers around the world. Our team supports deliveries (and pickups!) for Amazon Logistics, Same Day, Amazon Grocery, Lockers, and other new initiatives across the world.

In this role, your main focus will be to build algorithms, synthesize information, identify business opportunities, provide research direction, provide data-driven insights and communicate business and technical requirements within the team and across stakeholder groups. You will partner closely with other scientists and engineers in a collegial environment with a clear path to business impact. We have an exciting portfolio of research areas including vehicle routing, planning for electric and autonomous vehicles, district and stops planning, ultra-fast deliveries, fleet planning, and forecasting solutions for different delivery programs leveraging the latest OR, ML, and Generative AI methods, at a global scale. We are actively looking to hire scientists to lead one or more of these problem spaces. Successful candidates will have a deep knowledge of Operations Research and/or Machine/Deep Learning methods, experience in applying these methods to large-scale business problems, the ability to map models into production-worthy code in Python or Java, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big research challenges.

Mentorship & Career Growth
We care about your career growth! Whether your goals are to explore new technologies, take on bigger opportunities, or get to the next level, we'll help you get there. Our business is growing fast and our people will grow with it.


Key job responsibilities
* Invent and design new solutions for scientifically-complex problem areas and identify opportunities for invention in existing or new business initiatives.
* Successfully deliver large or critical solutions to complex problems in the support of medium-to-large business goals.
* Influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty.
* Apply mathematical optimization techniques, and/or machine/Gen-AI learning models to design solution methodologies to be used by in-house decision support tools and software.
* Research, prototype, simulate, and experiment with these models and participate in the production level deployment in Python or Java.
* Make insightful contributions to teams' roadmaps, goals, priorities, and approach.
* Actively engage with the internal and external scientific communities by publishing scientific articles and participating in research conferences.

- 2+ years of programming in Java, C++, Python or related language experience
- PhD, or Master's degree and 4+ years of science, technology, engineering or related field experience
- Experience building machine learning models or developing algorithms for business application
- 2+ years of hand-on experience in applying optimization methods for business application

- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- 3+ years of solving business problems through machine learning, data mining and statistical algorithms experience
- 3+ years of expertise in optimization: linear, non-linear, mixed-integer, large-scale, network, robust, stochastic, decomposition methods

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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 for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $222,200/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.