Careers

The Amazon Postdoctoral Science Program offers recent PhD graduates an exciting opportunity to gain hands-on industry experience, apply their specialized knowledge, and collaborate with Amazon's leading scientists. This program is designed for researchers who have completed their PhD within the past two years and are eager to bridge academia and industry, driving innovation at scale. “This program provides an excellent and fun opportunity to work on cutting-edge customer-obsessed research and learn from and collaborate with some of the brightest researchers and leading experts at Amazon,” said Sareh Nabi, a postdoctoral scientist in Amazon Ads who is participating in a postdoc pilot program. “It also provides a great platform to take the skillset I learned and apply it to a wide range of real-world applications on a large scale.” “This is an opportunity for outstanding researchers to work with us on our hardest scientific challenges,” said Jeremy Wyatt, senior manager of Amazon Robotics AI. “Amazon postdoctoral scientists will pursue exploratory work on our hardest problems, gaining industry experience and publishing the results in the best scientific venues.” Postdoctoral scientists will contribute to high-impact research initiatives, advance cutting-edge scientific developments, and publish their work in top-tier scientific journals. Participants will benefit from mentorship, access to Amazon's world-class resources, and exposure to real-world challenges with immediate customer impact. **Focus Areas** We are seeking candidates with expertise in foundational and applied research, particularly in: - Large Language Models (LLMs): Experience developing, fine-tuning, and scaling LLMs for diverse applications. - Graph Databases: Strong understanding of graph theory, data modeling, and implementation of graph database technologies in complex systems. - Mathematical Optimization: Good understanding of mathematical optimization, including mixed-integer optimization, combinatorial optimization, and robust optimization. **Basic Qualifications** - PhD in a relevant field (e.g., Computer Science, Operations Research, Mathematics, Statistics) received within 2 years of program start date. - Proven publication record in areas such as LLM, NLP, Generative AI, Graph Database, or other relevant domains. - Hands-on experience with technologies related to large language models, graph databases, and mathematical optimization. Preferred qualifications Postdocs demonstrate the following preferred job qualifications: - Ability to independently deliver results in a fast-paced environment - Publications at top-tier, peer-reviewed conferences and/or journals such as NurIPS, ICML, ICLR, CIKM, ICDE - Exceptional verbal and written communication skills - Expert knowledge in modeling and performance, operationalization, and scalability of scientific techniques and establishing decision strategies Required application materials: - CV, which lists all peer-reviewed publications and conferences - Research statement that outlines your research achievements and future research interests, and - A journal article or book chapter that demonstrates your domain expertise

As a Principal Applied Scientist, you are a trusted part of the technical leadership. You bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. You solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization. You are a hands-on scientific leader. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. You amplify your impact by leading scientific reviews within your organization or at your location. You scrutinize and review experimental design, modelling, verification and other research procedures. You probe assumptions, illuminate pitfalls, and foster shared understanding. You align teams toward coherent strategies. You educate, keeping the scientific community up to date on advanced techniques, state of the art approaches, the latest technologies, and trends. You help managers guide the career growth of other scientists by mentoring and play a significant role in hiring and developing scientists and leads. Key job responsibilities - Responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. - Develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. - Participate in organizational planning, hiring, mentorship and leadership development. - Technically ambitious with a passion for building scalable science and engineering solutions. - You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance). About the team Want to be part of the team whose mission is to expand Alexa to new countries, languages, devices and cultures? The Alexa International team makes it happen. Our customers are very diverse in where they live, the languages they speak to Alexa, the devices they use and the content that matters most. In turn our problems are diverse and need innovative solutions. Alexa International is at the nexus of all other Alexa teams and features, such as Smart Home, Music, News, ASR (Automatic Speech Recognition), NLU (Natural Language Understanding), Fire TV, Skills etc. We collaborate with hardware and software developers within and outside Amazon to build delightful experience for our customers. We’re working hard, having fun, and making history; come join us!

Stores Economics and Science (SEAS) is an interdisciplinary science and engineering team in Amazon's Stores organization with a peak-jumping mission: we apply expertise in science and engineering to move from local to global optima in methods, models, and software. We pursue this mission by leveraging frontier science; collaborating with partner teams; and learning from the tools, experience, and perspective of others. We scale by solving problems, first in the small to prove concepts, and then in the large by building scalable solutions. We also help other teams within Amazon scale by hiring and developing the best and embedding them in other business units. In 2024, we are focused on economics and science in areas related to (1) improving delivery speed and lowering cost-to-serve, (2) seller fees and incentives, and (3) emerging machine learning using LLMs. We also have some ongoing and highly leveraged collaborations that help partner teams inside Amazon short-circuit months of R&D or otherwise look around corners. We are looking for a seasoned Applied Science leader to build and deliver cutting-edge science and engineering solutions to improve our Stores business. In this role, you will lead a team of scientists and engineers with backgrounds in machine learning, NLP, IR, statistics, and economics to identify bottlenecks in our business, conceive new ideas to overcome those challenges, and deploy scientific solutions in partnership with product teams. Your responsibilities include developing the scientific models, benchmarks, and services. Graduate education and hands-on experience in machine learning, optimization, causal inference, Bayesian statistics, deep learning, or other quantitative scientific fields is a must. To be successful in this role, you should be a quick learner and comfortable with a high degree of ambiguity. Key job responsibilities Knowledge of causal inference and forecasting models are preferred. Practical knowledge of how we can leverage Transformers, LLMs, or other deep learning techniques for a variety of applications is a must.