Careers

日本の大学で機械学習や関連領域の研究に従事している学生の皆様に向けたフェローシッププログラムのご案内です。Amazon JapanのRetail Scienceチームでは、何百万人もの顧客にインパクトを与える価値あるテクノロジーに繋がるような、新しいプロトタイプやコンセプトを開発するプロジェクトに従事していただく学生を募集しています。プログラムは1ヶ月から3ヶ月の短期間のプロジェクトになります。 プロジェクトの対象となるテーマには、自然言語処理、表現学習、レコメンデーションシステム、因果推論といった領域が含まれますが、これらに限定されるわけではありません。プロジェクトは、チームのシニアサイエンティスト1名または複数名のガイダンスのもとで定義、遂行され、プロジェクト中は他のサイエンティストもメンターとしてフォローします。 学生の皆様が新しいモデルを考案したり、新しいテクノロジーを活用し実験する時間を最大化できるようにすることが目標です。そのため、プロジェクトではエンジニアリングやスケーリングよりも、プロトタイピングを行い具体的に概念実証を行うことに集中します。 また、Amazonでは論文出版も推奨しています。従事した研究開発活動の成果物として出版される論文には著者として参加することになります。 フェローシッププログラムは目黒の東京オフィスで、他のチームと一緒に行われます。Amazonは、プログラム期間中に必要なIT機器（ラップトップなど）、給与と通勤費を支給します。 Are you a current PhD student enrolled in a Japanese university researching Statistics, Machine Learning, Economics, or a related discipline? The Japan Retail Science team is looking for Fellows for short term (1-3 months) projects to develop new prototypes and concepts that can then be translated into meaningful technologies impacting millions of customers. In this position, you will be assigned a project to carry out from areas including but not limited to natural language processing, representation learning, recommender systems, or causal inference. The project will be defined and carried out under the supervision of one or more of our senior scientists, and you will be assigned another scientist as a mentor to follow you during the project. Our goal is to maximize the time you spend on inventing new models and experimenting with new techniques, so the work will concentrate on prototyping and creating a tangible proof of concept, rather than engineering and scaling. Amazon encourages publications, and you will be included as an author of any published manuscript. The fellowship will be carried out from our Tokyo office in Meguro together with the rest of the team. Amazon will provide the necessary IT equipment (laptop, etc.) for the duration of the fellowship, a salary, and commuting expenses. A day in the life - チームの多くのメンバーは、午前9時くらいから10時半くらいまでの間に仕事を始め、夕方6時から7時には仕事を終えています。出席が必要なミーティングに参加していれば、勤務時間は自由に決められます。 - パートタイムを希望する場合、勤務時間数は採用担当者とともに決定します。フルタイムの場合、労働時間は通常の契約通り週40時間となります。 - オフィスは目黒にあり、週3回の出社が必要です。残りの2日間はリモートワーク、オフィスへの出勤いずれも可能です。 - The majority of the team starts working between 9 and 10.30am until 18-19. You will have complete flexibility to determine your working hours as long as you are present for the meetings where your attendance is required. - Number of working hours will be determined together with the hiring manager in case you want to pursue the Fellowship part-time. In case of full-time, working hours will be 40/week as per a standard contract. - Our office is located in Meguro, and presence in the office is required 3 times/week. You are free to work remotely for the remaining two days or come to the office if you prefer. About the team 私たちのチームは、日本および世界のすべてのAmazonのベンダー企業に提供されるソリューションを支える製品を発明し、開発しています。私たちは、プロダクトマネージャーやビジネス関係者と協力し、科学的なモデルを開発し、インパクトのあるアプリケーションに繋げることで、Amazonのベンダー企業がより速く成長し、顧客により良いサービスを提供できるようにします。 私たちは、科学者同士のコラボレーションが重要であり、孤立した状態で仕事をしても、幸せなチームにはならないと考えています。私たちは、科学者が専門性を高め、最先端の技術についていけるよう、社内の仕組みを通じて継続的に学ぶことに重きを置いています。私たちの目標は、世界中のAmazonのベンダーソリューションの主要なサイエンスチームとなることです。 Our team invents and develops products powering the solutions offered to all Amazon vendors, in Japan and worldwide. We interact with Product Managers and Business stakeholders to develop rigorous science models that are linked to impactful applications helping Amazon vendors grow faster and better serving their customers. We believe that collaboration between scientists is paramount, and working in isolation does not lead to a happy team. We place strong emphasis on continuous learning through internal mechanisms for our scientists to keep on growing their expertise and keep up with the state of the art. Our goal is to be primary science team for vendor solutions in Amazon, worldwide. We are open to hiring candidates to work out of one of the following locations: Tokyo, 13, JPN

日本の大学で機械学習や関連領域の研究に従事している学生の皆様に向けたフェローシッププログラムのご案内です。Amazon JapanのRetail Scienceチームでは、何百万人もの顧客にインパクトを与える価値あるテクノロジーに繋がるような、新しいプロトタイプやコンセプトを開発するプロジェクトに従事していただく学生を募集しています。プログラムは1ヶ月から3ヶ月の短期間のプロジェクトになります。 プロジェクトの対象となるテーマには、自然言語処理、表現学習、レコメンデーションシステム、因果推論といった領域が含まれますが、これらに限定されるわけではありません。プロジェクトは、チームのシニアサイエンティスト1名または複数名のガイダンスのもとで定義、遂行され、プロジェクト中は他のサイエンティストもメンターとしてフォローします。 学生の皆様が新しいモデルを考案したり、新しいテクノロジーを活用し実験する時間を最大化できるようにすることが目標です。そのため、プロジェクトではエンジニアリングやスケーリングよりも、プロトタイピングを行い具体的に概念実証を行うことに集中します。 また、Amazonでは論文出版も推奨しています。従事した研究開発活動の成果物として出版される論文には著者として参加することになります。 フェローシッププログラムは目黒の東京オフィスで、他のチームと一緒に行われます。Amazonは、プログラム期間中に必要なIT機器（ラップトップなど）、給与と通勤費を支給します。 Are you a current PhD student enrolled in a Japanese university researching Statistics, Machine Learning, Economics, or a related discipline? The Japan Retail Science team is looking for Fellows for short term (1-3 months) projects to develop new prototypes and concepts that can then be translated into meaningful technologies impacting millions of customers. In this position, you will be assigned a project to carry out from areas including but not limited to natural language processing, representation learning, recommender systems, or causal inference. The project will be defined and carried out under the supervision of one or more of our senior scientists, and you will be assigned another scientist as a mentor to follow you during the project. Our goal is to maximize the time you spend on inventing new models and experimenting with new techniques, so the work will concentrate on prototyping and creating a tangible proof of concept, rather than engineering and scaling. Amazon encourages publications, and you will be included as an author of any published manuscript. The fellowship will be carried out from our Tokyo office in Meguro together with the rest of the team. Amazon will provide the necessary IT equipment (laptop, etc.) for the duration of the fellowship, a salary, and commuting expenses. A day in the life - チームの多くのメンバーは、午前9時くらいから10時半くらいまでの間に仕事を始め、夕方6時から7時には仕事を終えています。出席が必要なミーティングに参加していれば、勤務時間は自由に決められます。 - パートタイムを希望する場合、勤務時間数は採用担当者とともに決定します。フルタイムの場合、労働時間は通常の契約通り週40時間となります。 - オフィスは目黒にあり、週3回の出社が必要です。残りの2日間はリモートワーク、オフィスへの出勤いずれも可能です。 - The majority of the team starts working between 9 and 10.30am until 18-19. You will have complete flexibility to determine your working hours as long as you are present for the meetings where your attendance is required. - Number of working hours will be determined together with the hiring manager in case you want to pursue the Fellowship part-time. In case of full-time, working hours will be 40/week as per a standard contract. - Our office is located in Meguro, and presence in the office is required 3 times/week. You are free to work remotely for the remaining two days or come to the office if you prefer. About the team 私たちのチームは、日本および世界のすべてのAmazonのベンダー企業に提供されるソリューションを支える製品を発明し、開発しています。私たちは、プロダクトマネージャーやビジネス関係者と協力し、科学的なモデルを開発し、インパクトのあるアプリケーションに繋げることで、Amazonのベンダー企業がより速く成長し、顧客により良いサービスを提供できるようにします。 私たちは、科学者同士のコラボレーションが重要であり、孤立した状態で仕事をしても、幸せなチームにはならないと考えています。私たちは、科学者が専門性を高め、最先端の技術についていけるよう、社内の仕組みを通じて継続的に学ぶことに重きを置いています。私たちの目標は、世界中のAmazonのベンダーソリューションの主要なサイエンスチームとなることです。 Our team invents and develops products powering the solutions offered to all Amazon vendors, in Japan and worldwide. We interact with Product Managers and Business stakeholders to develop rigorous science models that are linked to impactful applications helping Amazon vendors grow faster and better serving their customers. We believe that collaboration between scientists is paramount, and working in isolation does not lead to a happy team. We place strong emphasis on continuous learning through internal mechanisms for our scientists to keep on growing their expertise and keep up with the state of the art. Our goal is to be primary science team for vendor solutions in Amazon, worldwide. We are open to hiring candidates to work out of one of the following locations: Tokyo, 13, JPN

As a Senior Data Scientist with expertise in Machine Learning (ML), development and use of multi-model models, utilizing diverse sets of large data you will work with a team of Applied Scientists and Software Engineers to build innovative foundation models for robotic manipulation utilizing computer vision and scene perception technology. Your role will focus first on feature engineering, data collection and data usage from large data sets across Fulfillment Technologies and Robotics (FTR), with an eye on strategy going forward to unify a data strategy across organizations. This position requires high levels of analytical thinking, ability to quickly approach large ambiguous problems and apply analytics, technical and engineering expertise to rapidly analyze, validate, visualize, prototype and deliver solutions. Key job responsibilities - Utilize expertise in feature engineering on massive data sets through exploratory data analysis across existing large data sets in Fulfillment Technologies and Robotics (FTR). Help identify areas where we could create new data sources that would improve training capabilities based on understanding of how different scenes in FCs could impact the trained model and ultimately performance of robotic manipulation. - Identify data requirements, build methodology and data modeling strategy across the diverse data sets for both short-term and long-term needs - Work closely with Applied Scientists in building FM solutions, ensuring that the data strategy fits the experimentation paths, as well as contribute to the FM strategy through identifying opportunities based on the data - Work with and develop large datasets (training/fine tuning) and bring large datasets together to inform both training in FOMO as well as across FTR - Design and implement data solutions, working closely with engineers to guide on best paths for building data pipelines and infrastructure for model training - Collaborate across teams both within and outside of FOMO on data strategy A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

Are you interested in changing the Digital Reading Experience? We are from Kindle Books Team looking for a set of Scientists to take the reading experience in Kindle to next level with a set of innovations! We envision Kindle as the place where readers find the best manifestation of all written content optimized with features that enable them to get the most out of reading, and creators are able to realize their vision to customers quickly and at scale. Every time customers open their content, regardless of surface, they start or restart their reading in a familiar, useful and engaging place. We achieve this by building a strong foundation of core experiences and act as a force multiplier and partner for content creators (directly or indirectly) to easily innovate on top of Kindle's purpose built content experience stack in a simple and extensible way. We will achieve this by providing a best-in-class reading experience, unique content experiences, and remaining agile in meeting the evolving needs and preferences of our users. Our goal is to foster long-lasting reading habits and make us the preferred destination for enriching literary experiences. We are building a In The Book Science team and looking for Scientists, who are passionate about Reading and are willing to take Reading to the next level. Every Book is a complex structure with different entities, layout, format and semantics, with more than 17MM eBooks in our catalog. We are looking for experts in all domains like core NLP, Generative AI, CV and Deep Learning Techniques for unlocking capabilities like analysis, enhancement, curation, moderation, translation, transformation and generation in Books based on Content structure, features, Intent & Synthesis. Scientists will focus on Inside the book content and semantically learn the different entities to enhance the Reading experience overall (Kindle & beyond). They have an opportunity to influence in 2 major phases of life-cycle - Publishing (Creation of Books process) and Reading experience (building engaging features & representation in the book thereby driving reading engagement). Key job responsibilities - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 2+ years of applied research experience - Knowledge of programming languages such as C/C++, Python, Java or Perl - Experience programming in Java, C++, Python or related language - You have expertise in one of the applied science disciplines, such as machine learning, natural language processing, computer vision, Deep learning - You are able to use reasonable assumptions, data, and customer requirements to solve problems. - You initiate the design, development, execution, and implementation of smaller components with input and guidance from team members. - You work with SDEs to deliver solutions into production to benefit customers or an area of the business. - You assume responsibility for the code in your components. You write secure, stable, testable, maintainable code with minimal defects. - You understand basic data structures, algorithms, model evaluation techniques, performance, and optimality tradeoffs. - You follow engineering and scientific method best practices. You get your designs, models, and code reviewed. You test your code and models thoroughly - You participate in team design, scoping and prioritization discussions. You are able to map a business goal to a scientific problem and map business metrics to technical metrics. - You invent, refine and develop your solutions to ensure they are meeting customer needs and team goals. You keep current with research trends in your area of expertise and scrutinize your results. A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test solutions to improve our experience. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, model development and productionizing the same. You will mentor other scientists, review and guide their work, help develop roadmaps for the team. We are open to hiring candidates to work out of one of the following locations: Bangalore, IND | Bangalore, KA, IND

At Amazon we strive to be earth’s most customer centric company and we are one of the core science teams in CS org tasked with the mission to making this happen. Are you curious about new platforms and technologies and have a desire to deliver world-class customer service? Are you excited by the idea of owning a problem and innovating on behalf of customers? Can you deal with ambiguity and keep up with the pace of a company whose cycles are measured in weeks, not years? D2 Science & Analytics team is seeking an Applied Scientist to develop cutting-edge AI solutions leveraging LLM, ML and NLP techniques to understand and resolve customer issues and provide earth's best customer service. We are looking for individuals with a passion for learning, researching, and deploying production-ready science solutions in a highly collaborative environment. We like to ideate, experiment, iterate, optimize and scale quickly, while thoughtfully balancing speed and quality. If you have experience with two or more of the following, · Research and implementation of multi-turn task-oriented dialogue systems · Natural Language Understanding / Spoken Language Understanding · Information Retrieval, Question Answering, Semantic Representation · Zero-shot or Few-shot Learning · Crowdsourced NLU annotation best practices · Reinforcement Learning (preferably in an NLP application) · Computational Linguistics · Large scale text classification then we want to hear from you! Responsibilities: - Drive collaborative research and creative problem solving - Apply scientific concepts to real-world business problems - Create experiments and prototype implementations of new learning algorithms and prediction techniques - Collaborate with engineering teams to design and implement software solutions for science problems - Constructively critique peer research and mentor junior s and engineers A day in the life If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skill sets. If you’re passionate about this role and want to make an impact on a global scale, please apply!”Benefits Summary: “Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan” We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

AWS AI Research and Engineering (AIRE) is looking for world class scientists and engineers to work on the development of autonomous AI agents. At AWS AI/ML you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and innovate on new learning techniques. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. Large-scale foundation models have been the powerhouse in many of the recent advancements in computer vision, natural language processing, automatic speech recognition, recommendation systems, and time series modeling. Developing such models requires not only skillful modeling in individual modalities, but also understanding of how to seamlessly combine them, and how to scale the modeling methods to learn with huge models and on large datasets. We seek a strong technical leader with domain expertise in machine learning, large language models and multimodal models, reinforcement learning and setting up simulation environments to benchmark and evaluate. A day in the life Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices. AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services. We are open to hiring candidates to work out of one of the following locations: New York, NY, USA

Does the idea of creating technology solutions for delivering 11 Billion+ packages across the globe excite you? If yes, come join a fun-loving, diverse, and creative team at Amazon Last Mile! The vision of the team is "To create Earth’s safest, most adaptive, and efficient plans for Last Mile logistics". The Last Mile Delivery Technology team is instrumental in impacting customer satisfaction directly, by devising innovative ways to deliver packages quickly and cost-effectively to the customers, and at scale using Artificial Intelligence (AI), Machine Learning and Operations Research solutions. Last Mile Delivery Technology organization supports the design, planning and execution of last mile transportation for Amazon’s various parcel and grocery delivery programs. All these programs require a large number of decision support systems to operate at scale and serve our customers, spanning demand planning, jurisdiction planning, delivery channel and network design, capacity planning for on the road and under the roof at delivery stations, routing inputs and route optimization. While these decision support systems have thus far been approached through the lens of traditional optimization and machine learning, we are looking to re-envision this space and pursue Foundational AI research, to innovate and advance the state of these decision support systems. Specifically, we are looking to develop foundational models (including Large Language Models, Multimodal Language Models, Multimodal Models), and adaptations to serve last mile use cases. Beyond Amazon the work developed will spur new fundamental knowledge and innovation in the logistics space. We are looking for candidates with knowledge and experience in designing and developing state-of-art AI solutions (including development and application of advanced deep learning algorithms, foundational models, multimodal generative AI solutions, reinforcement learning), to join our team. Demonstrated experience scaling and optimizing the training and inference of these models, building real world solutions, to meet the customer use cases is preferred. Proven track record of publishing in major AI conferences and demonstrated experience working in industry will be preferred. Key job responsibilities Candidates will be responsible for developing Foundational AI solutions, to serve the myriad of decision support use cases across last mile. In this role, you will be expected to define new research avenues, explore, adopt, and invent new machine learning techniques, implement scalable science and engineering solutions, contribute software to production systems, conduct rigorous experiments, publish results, influence technical and business leadership and ensuring that research is translated into practice. You will be working with a team of scientists and engineers, helping shape the strategic and tactical vision, and contribute hands on to foundational research efforts in last mile. A day in the life Sitting at the core of Amazon’s Last Mile business, Routing and Planning (RaP) invents technology solutions that deliver toward the RaP vision: to create earth’s safest, most adaptive, and efficient plans for Last Mile logistics. RaP serves a diverse set of external and internal customers. For Amazon End Customers and transporters, we build solutions to deliver 11B packages and services to arrive at the right place and time, while meeting the growing preference for speed and precision. For internal customers, we build and delivery routing solutions Worldwide adding up to a $1B USD, across multiple amazon businesses ranging from Amazon Logistics, Amazon X-tra Large to Same/Sub-Same Day Deliveries, Fresh and Groceries etc using multiple mode of transports. If the opportunity to innovate, create and deliver first-time solutions alongside world-class engineers and scientists e.g. building a new delivery foundational model from scratch utilizing data at an unprecedented scale in the industry excites you, this is the place for you. About the team The Last Mile (LM) Science organization serves two primary functions: (1) maintaining and enhancing the components which provide the essential intelligence in nearly every LM system, and (2) creating the science which will enable the continued growth of Amazon in the future. The systems used on a daily basis by the Last Mile to deliver packages from the station to the customer’s doorstep contains embedded models developed by the science team, or relies on inputs derived from these models. These models determine how efficiently Amazon can serve its customers and at what cost. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA

Selling Partner Promotions is seeking a Sr. Economist to use econometric and machine learning techniques to help offer Customers high quality deals and promotions. This role will be a key member of a team of scientists supporting the Pricing and Promotions related business. The Sr. Economist will work closely with other research scientists, machine learning experts, and economists to design and run experiments, research new algorithms, and find new ways to improve Seller Pricing and Promotions to optimize the Customer experience. Key job responsibilities - Build economic models to quantify the causal impact of pricing actions and promotions on customers and sellers. - Build models to define, measure and optimize for high quality deals - Define and execute an extensive experimental roadmap to test hypotheses and validate the outputs of models. - Create models that allow an optimization of selling partner ROI and customer long-term value. - Evaluate and validate the proposed models via offline benchmark tests as well as online A/B tests in production. - Publish and present your work at internal and external scientific venues. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

The Amazon Artificial Generative Intelligence (AGI) team in India is seeking a talented, self-driven Applied Scientist to work on prototyping, optimizing, and deploying ML algorithms within the realm of Generative AI. Key job responsibilities - Research, experiment and build Proof Of Concepts advancing the state of the art in AI & ML for GenAI. - Collaborate with cross-functional teams to architect and execute technically rigorous AI projects. - Thrive in dynamic environments, adapting quickly to evolving technical requirements and deadlines. - Engage in effective technical communication (written & spoken) with coordination across teams. - Conduct thorough documentation of algorithms, methodologies, and findings for transparency and reproducibility. - Publish research papers in internal and external venues of repute - Support on-call activities for critical issues We are open to hiring candidates to work out of one of the following locations: Bengaluru, KA, IND

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