Description

The Routing and Planning organization supports all parcel and grocery delivery programs across Amazon Delivery. All these programs have different characteristics and require a large number of decision support systems to operate at scale. As part of Routing and Planning organization, you’ll 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 network optimization, routing, routing inputs, electric vehicles, delivery speed, capacity planning, geospatial planning and dispatch solutions for different last mile programs leveraging the latest OR, ML, and Generative AI methods, at a global scale. We are actively looking to hire senior scientists to lead one or more of these problem spaces. Successful candidates will have a deep knowledge of Operations Research and Machine 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.

Inclusive Team Culture

Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which reminds team members to seek diverse perspectives, learn and be curious, and earn trust.

Mentorship & Career Growth

We care about your career growth too. 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.

• Drive or heavily 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 algorithms to design optimal or near optimal 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.

• Lead project plans from a scientific perspective by managing product features, technical risks, milestones and launch plans.

• Make insightful contributions to organization's roadmaps, goals, priorities, and approach.

• Actively engage with the internal and external scientific communities by publishing scientific articles and participating in research conferences.

We are open to hiring candidates to work out of one of the following locations:

Austin, TX, USA | Bellevue, WA, USA

Basic Qualifications

• PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 10+ years of industry or academic research experience

• Experience programming in Java, C++, Python or related language

• 3+ years of building machine learning models or developing algorithms for business application experience

• Experience with conducting research in a corporate setting

• Expertise in optimization: linear, non-linear, mixed-integer, large-scale, network, robust, stochastic, decomposition methods

Preferred Qualifications

• 5+ years of building machine learning models or developing algorithms for business application experience

• Experience using managed ML/AI solutions

• Experience in designing and supporting large-scale optimization systems in a production environment

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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

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 $260,000/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.