Careers

Disrupting the way Amazon fulfills our customers’ orders. Amazon operations is changing the way we improve Customer Experience through flawless fulfillment focused on 1) successful on-time delivery, 2) at speed and 3) at the lowest possible cost. Being the engine of Amazon Operational excellence, driving zero defects through ideal operation, being the heart of the Fulfillment network and its center of excellence, being proactive and aspiring for zero defects across the network with 100% organizational engagement. For example, our applied science team leverage a variety of advanced machine learning and cloud computing techniques to power Amazon's operations performance management. This includes building algorithms and cloud services using LLMs, deep neural networks, and other ML approaches to make root cause analysis of incidents and defects better. They develop machine learning models to predict inbound capacity forecasts and select the optimal order of unloading and stowing the incoming items in the Fulfilment Center. The teams also utilize Langchain, Amazon Bedrock, Amazon Textract, ElasticCache Redis, Opensearch and Kubernetes to extract insights from big data and deliver recommendations to operations managers, continuously improving through offline analysis and impact evaluation. Underpinning these efforts are unique technical challenges, such as operating at unprecedented scale (100k requests per second with SNS/SQS and <1ms latency with Redis) while respecting privacy and customer trust guarantees, and solving a wide variety of complex computational operational problems related to inbound management for unloading and stowing before stow time SLA, outbound for picking and packing before SLAM PAD time and shipping for staging and loading before Critical Pull Time. Key job responsibilities GOX team is looking for a Senior Applied Scientist to support our vision of giving our customers the best fulfillment experience in the world, and our mission of delighting our customers by providing capabilities, tools and mechanisms to fulfillment operations. As Skynet Sr. APSCI, you would be providing resources and expertise for all data related reports (dashboard, scorecards…), analysis (statistical approach), and Machine Learning products and tools development. On top of your internal customers within GOX team you would be supporting more widely with your experience and skills all across the org, partnering with a wide range of departments within Ops Integration (Packaging, Sustainability) within the company mainly with ICQA, ATS, AMZL, GTS… on several projects. You will be part of the community of Scientists within Amazon Operations including other AS, BIEs, SDEs, … split across the different departments. You will be part of projects requiring your close collaboration and interactions with Operations that require you to have a good understanding of product flow and process all along the distribution chain. The GOX team is now recognized for its expertise and excellence in creating tools that improve massively the customer experience. Several of them now rolled out in other regions with some of these tools becoming worldwide standard. Reporting to the GOX Senior Manager, you will be responsible for developing the data-driven decision process from historical data and ML based predictive analysis and maintaining accurate and reliable data infrastructure. You will work across the entire business, and be exposed to a wide range of functions from Operations, Finance, Technology, and Change management. The successful candidate will be able to work with minimal instruction and oversight, manage multiple tasks and support projects simultaneously. Maintaining your relationships with the customers in operations and within the team, while owning deliverables end-to-end is expected. Critical to the success of this role is your ability to work with big data, develop insightful analysis, communicate findings in a clear and compelling way and work effectively as part of the team, raising the bar and insisting on high standards. About the team GOX DEA team is the engine of Amazon Operational excellence at the heart of the fulfillment network operations, aspiring zero defects. It is our purpose to improve Customer Experience through flawless fulfillment focused on 1) successful on-time delivery, 2) at speed and 3) at the lowest possible cost. Our Solutions support on-time delivery of billions of packages to our customers across the globe leveraging AI & Generative AI technology.

We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You’ll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. If you’re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!

Amazon’s Last Mile Team is looking for a passionate individual with strong optimization and analytical skills to join its Last Mile Science team in the endeavor of designing and improving the most complex planning of delivery network in the world. Last Mile builds global solutions that enable Amazon to attract an elastic supply of drivers, companies, and assets needed to deliver Amazon's and other shippers' volumes at the lowest cost and with the best customer delivery experience. Last Mile Science team owns the core decision models in the space of jurisdiction planning, delivery channel and modes network design, capacity planning for on the road and at delivery stations, routing inputs estimation and optimization. Our research has direct impact on customer experience, driver and station associate experience, Delivery Service Partner (DSP)’s success and the sustainable growth of Amazon. Optimizing the last mile delivery requires deep understanding of transportation, supply chain management, pricing strategies and forecasting. Only through innovative and strategic thinking, we will make the right capital investments in technology, assets and infrastructures that allows for long-term success. Our team members have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, scientists, and software engineers in the industry. Key job responsibilities Candidates will be responsible for developing solutions to better manage and optimize delivery capacity in the last mile network. The successful candidate should have solid research experience in one or more technical areas of Operations Research or Machine Learning. These positions will focus on identifying and analyzing opportunities to improve existing algorithms and also on optimizing the system policies across the management of external delivery service providers and internal planning strategies. They require superior logical thinkers who are able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. To support their proposals, candidates should be able to independently mine and analyze data, and be able to use any necessary programming and statistical analysis software to do so. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs.

Project Kuiper is an initiative to increase global broadband access through a constellation of 3,236 satellites in low Earth orbit (LEO). Its mission is to bring fast, affordable broadband to unserved and underserved communities around the world. Project Kuiper will help close the digital divide by delivering fast, affordable broadband to a wide range of customers, including consumers, businesses, government agencies, and other organizations operating in places without reliable connectivity. The Kuiper Global Capacity Planning team owns designing, implementing, and operating systems that support the planning, management, and optimization of Kuiper network resources worldwide. We are looking for a talented principal scientist to lead Kuiper’s long-term vision and strategy for capacity simulations and inventory optimization. This effort will be instrumental in helping Kuiper execute on its business plans globally. As one of our valued team members, you will be obsessed with matching our standards for operational excellence with a relentless focus on delivering results. Key job responsibilities In this role, you will: Work cross-functionally with product, business development, and various technical teams (engineering, science, R&D, simulations, etc.) to establish the long-term vision, strategy, and architecture for capacity simulations and inventory optimization. Design and deliver modern, flexible, scalable solutions to complex optimization problems for operating and planning satellite resources. Lead short and long terms technical roadmap definition efforts to predict future inventory availability and key operational and financial metrics across the network. Design and deliver systems that can keep up with the rapid pace of optimization improvements and simulating how they interact with each other. Analyze large amounts of satellite and business data to identify simulation and optimization opportunities. Synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication to drive change across Kuiper. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day. We optimize product placements using a combination of machine learning and natural language processing (NLP) algorithms operating in low latency, high-volume systems. We are highly motivated, collaborative and fun-loving, with entrepreneurial drive and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. We are looking for an Applied Scientist to join the Whole-page Advertising Experiences (Waves) team in Marketplace Intelligence with a broad mandate to experiment and innovate to grow Sponsored Products. As an Applied Scientist on this team, you will help to identify unique opportunities to create customized and delightful shopping experience for our growing marketplaces worldwide. Your job will be to identify big opportunities for the team that can help to grow Sponsored Products business working with search and retail partner teams, software engineers and product managers. You will have the opportunity to design, run, and analyze A/B experiments that improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact. More importantly, you will have the opportunity to broaden your technical skills in an environment that thrives on creativity, experimentation, and product innovation. Key job responsibilities - Be the technical leader in Machine Learning; lead efforts within this team and across other teams. - Perform hands-on analysis and modeling of enormous data sets to develop insights that both improve the shopper experience while increasing traffic monetization and merchandise sales. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Research new and innovative machine learning approaches. - Recruit Scientists to the team and provide mentorship.

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by protecting Amazon customers from hackers and bad actors? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer every day? Are you excited by the prospect of analyzing and modeling terabytes of data and create state-of-art algorithms to solve real world problems? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Amazon Account Integrity team. The Amazon Account Integrity team works to ensure that customers are protected from bad actors trying to access their accounts. Our greatest challenge is protecting customer trust without unjustly harming good customers. To strike the right balance, we invest in mechanisms which allow us to accurately identify and mitigate risk, and to quickly correct and learn from our mistakes. This strategy includes continuously evolving enforcement policies, iterating our Machine Learning risk models, and exercising high‐judgement decision‐making where we cannot apply automation. Main responsibilities - Use statistical and machine learning techniques to create scalable risk management systems - Analyzing and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends - Design, development and evaluation of highly innovative models for risk management - Working closely with software engineering teams to drive real-time model implementations and new feature creations - Working closely with operations staff to optimize risk management operations - Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Tracking general business activity and providing clear, compelling management reporting on a regular basis - Research and implement novel machine learning and statistical approaches

We are seeking an Applied Scientist to join our AI Security team, which builds security tooling and paved path solutions to ensure Generative AI (GenAI) based experiences developed by Amazon uphold our high security standards, and uses AI to develop foundational services that make security mechanisms more effective and efficient. As an Applied Scientist, you’ll be responsible for designing and implementing state-of-the-art solutions, to build an AI-based foundational service for securing products and services at Amazon scale. You will collaborate with applied scientists and software engineers to develop innovative technologies to solve some of our hardest security problems, and AI-based security solutions that support builder teams across Amazon throughout their software development journey, enabling Amazon businesses to strengthen their security posture more efficiently and effectively. Key job responsibilities • design and implement accurate and scalable methods to solve our hardest AI security problems • Lead and partner with applied scientists and software development engineers to drive technical design and implementation for a foundational GenAI-based security service About the team The mission of the AI Security organization is to ensure Generative AI experiences delivered by Amazon to our customers uphold our high security standards and to harness AI to strengthen Amazon’s security posture more efficiently and effectively. A day in the life A day in the life involves meeting Vulnerability Management and Incident Responder teams to review data flows, prediction use cases, and automation gaps. From here you will research data sets, working with security/software engineers to retrieve data needed for your analysis and explorations. Once you have framed the problems, you will conduct experiments, regressions, and various analysis activities to find insights. You will develop and train models that will then be placed into a production environment with the help of software engineers. You will then work with your security team partners to understand the effectiveness of the models created. About the team The Defensive Security team is small, tight-knit, and located in Austin, Texas. It is primarily software engineers, but will be developed into a hybrid team of software engineers and security engineers. This team will have tenured Amazonian leadership, with a track record of mentoring, coaching, and career progression support. About Amazon Security Diverse Experiences — Amazon Security 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 Amazon Security? — At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture — In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Amazon is hiring a Principal Applied Scientist (PAS) to join the Search and Conversational Shopping AI team. In this role, you will be responsible for the architectural design and technological advancements of the customer experience of Amazon Rufus, our next-generation, AI-driven search and shopping assistant. This innovative role focuses on developing innovative search and shopping experiences, utilizing large language models, generative AI, and advanced machine learning technologies. Key job responsibilities As a Principal Applied Scientist in Search, you will possess deep expertise in machine learning and data science, with specializations in information retrieval, recommendations, ranking, large language models, and generative AI across various modalities. The role involves solution alignment across multiple partners, such as front-end, relevance, ranking, and personalization teams. You will collaborate with teams of scientists and engineers to translate business and functional requirements into concrete deliverables, leading strategic efforts to enhance upper funnel search customer experiences. You will design integrated solutions efficiently delivered across all contributing stakeholder teams, driving alignment among these tech teams in the short term and influencing their future roadmaps in the long term to support our experimentation roadmap. Responsible for overall solution quality, this role will focus on improving experimentation velocity and, in the future, facilitating partner development on upper funnel customer experiences. This role ensures we are building scalable solutions with smart checks on data quality centrally, navigating the ambiguity inherent in this new area. You will make critical judgements to select the best technical solutions for both short and long-term experimentation objectives, bringing clarity from ambiguity, structuring tradeoff decisions, and effectively communicating on technically contentious topics. Finally, you will engage with academic partners to augment our in-house talent with access to the latest research and expert mentoring. About the team The vision of the Search and Conversational Shopping AI Team is to revolutionize the search and shopping experience through technological innovations in advanced AI and machine learning. We focus on enhancing query understanding, navigational and upper funnel search, developing LLM-based AI assistants, and more. Our goal is to create intuitive, personalized search interfaces that seamlessly connect customers with products, enhancing satisfaction, engagement, and transforming e-commerce interactions.

-- This role is open for NYC and SEA locations -- Want to work on one of the highest priorities across Amazon Ads? This is your chance to help build a billion dollar business, innovate on a new product space, and have a positive impact on millions of views while working with industry-leading technologies. The Ad Catalyst team in Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital advertising solutions to over a million advertisers with the goal of helping our our hundreds of millions customers find and discover anything they want to buy. We start with the customer and work backwards in everything we do, including advertising. Our team owns researching, evaluating, ranking and serving personalized recommendation to each of our 1+ million advertisers using state of the art machine learning techniques ( e.g., deep learning, deep-reinforcement learning, causal modeling). Our team is placed centrally in the Advertising Experience organization which owns the advertising console, this provides us full-stack ownership giving scientists the satisfaction of seeing their work directly power advertiser experiences with measurable outcomes. If you’re interested in joining a rapidly growing team working to build a unique, highly respected advertising group with a relentless focus on the customer, you’ve come to the right place. This is a unique opportunity to get in early and drive significant portions of the technical roadmap and shape the research agenda of a billion+ dollar business. Successful candidates will have strong technical ability, focus on customers by applying a customer-first approach, excellent teamwork and communication skills, and a motivation to achieve results in a fast-paced environment through both strong personal delivery and the ability to develop partnerships with science teams across the org. Our position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. If you are selected, you have the opportunity to make a difference to our business by designing and building state of the art machine learning systems on big data, leveraging Amazon’s vast computing resources (AWS), working on exciting and challenging projects, and delivering meaningful results to customers world-wide. Key job responsibilities - Be a thought leader and forward thinker, anticipating obstacles to success, helping avoid common failure modes, and holding us to a high standard of technical rigor and excellence in machine learning (ML). - Own and drive the most complex and strategic solutions across the business; responsible for many millions in revenue. - Own the dialogue with partner science teams - shape consensus in scientific research roadmap, modeling approaches evaluation and presentation of the science driven results to our advertisers. - Define evaluation methods and metrics that measure the effectiveness of advertising recommendations using a variety of science techniques (Randomized Control Trials, Causal Modeling, Reinforcement learning policy evaluation) - Research, build, and deploy innovative ML solutions; working across all technical disciplines. - Identify untapped, high-risk technical and scientific directions, and stimulate new research directions that you will deliver on. - Be responsible for communicating our ML innovations to the broader internal & external scientific communities. - Hire, mentor, and guide scientists. - Partner with engineering leaders to build efficient and scalable solutions. We are open to hiring candidates to work out of one of the following locations: New York, Seattle

Are you interested in helping build a world-class transportation network for Amazon as we delight our customers with more 1 day promises and also meet our sustainability targets ? Do you want to deliver products at scale influence the network design of one of the most complex transportation network in the world? Amazon Worldwide Operations is looking for a Data Scientist. The role will require modeling, auditing and optimizing our transportation network from our fulfillment centers to our last mile carriers who deliver packages to customers. To be successful in the role, you need strong analytical skills, excellent communication skills, ability to influence across business functions and manage stakeholders’ expectations effectively. You will work in a fast-paced environment that requires you to be detail-oriented and comfortable in working with multiple business and technical teams. This position has the option to be located in Bellevue WA, Austin TX, Nashville TN, Santa Monica CA, Arlington VA, New York City NY, or Toronto CA. Key job responsibilities - Development of scalable data science solutions to audit and optimize our transportation network. - Development and execution of analytical tools to model our transportation network. - Contribute to the strategy for network design, prioritize technical and operational initiatives, evaluate and set stakeholders expectations.