Careers

Amazon is hiring a Senior Applied Scientist within Customer Forecasting and Valuation (CFV). CFV owns several of the primary decision metrics Amazon uses to evaluate launches and investments — causal estimates of how customer actions today translate into customer value over the year ahead. These metrics are how Amazon works backwards from the customer at scale: they let thousands of launch decisions a year, across Retail, Ads, Marketing, and Selection, weigh short-term profitability against long-term growth. We are in the middle of a generational rebuild of how these metrics are produced. Our team is developing transformer-based foundation models of customer behavior, learned directly from billions of behavioral events. They are being built as shared infrastructure: one learned representation of customer behavior that a wide range of measurement and optimization systems across Amazon can be built on top of. CFV is part of the Customer Behavior Analytics (CBA) organization, which builds the tools used to understand customer behavior and value generation across Amazon's Retail business. As a Senior Applied Scientist you are working at the intersection of causal inference, sequence modeling, and experimentation. The work spans methodological invention — making learned representations estimation-aware, closing the loop between experimental ground truth and model training, extrapolating short-horizon observations into year-ahead causal effects — and translation of that work into production systems that move real launch decisions. You will partner with other senior scientists, product owners, and business leaders, and you will work closely with a dedicated engineering team. The right candidate has deep expertise in ML and causal inference, judgment about when to invent versus reuse, and the appetite to operate in ambiguity. If you want to be part of a team that is shaping how Amazon measures the value of what it does for customers, and how it balances short-term profitability with long-term growth, we should talk.

The Worldwide Design Engineering (WWDE) organization delivers innovative, effective and efficient engineering solutions that continually improve our customers’ experience. WWDE optimizes designs throughout the entire Amazon value chain providing overall fulfillment solutions from order receipt to last mile delivery. We are seeking a Sr. Simulation Scientist to assist in designing and optimizing the fulfillment network concepts and process improvement solutions using discrete event simulations for our World Wide Design Engineering Team. Successful candidates will be technical expert and natural self-starter who have the drive to apply simulation and optimization tools to solve complex flow and buffer challenges during the development of next generation fulfillment solutions. The Simulation Scientist is expected to deep dive into complex problems and drive relentlessly towards innovative solutions working with cross functional teams. Be comfortable interfacing and influencing various functional teams and individuals at all levels of the organization in order to be successful. Lead strategic modelling and simulation projects related to system simulation, optimization, AI powered simulation, advanced simulation tools development, coding simulation algorithms to drive process design decisions. Key job responsibilities - You influence the scientific strategy across multiple teams in your business area. You support go/no-go decisions, build consensus, and assist leaders in making trade-offs. You proactively clarify ambiguous problems, scientific deficiencies, and where your team’s solutions may bottleneck innovation for other teams. - Lead the design, implementation, and delivery of the simulation science solutions to perform system of systems discrete event simulations for significantly complex operational processes that have a long-term impact on a product, business, or function using FlexSim, Demo 3D, AnyLogic or any other Discrete Event Simulation (DES) software packages, AI powered simulation tools, PLC/IPC Emulations, Robotic system simulation and emulation - Lead strategic system modelling and simulation projects using DES tools, software, PLC/IPC emulations, to drive process design decisions - Be an exemplary practitioner in simulation data science discipline to establish best practices and simplify problems to develop discrete event simulations faster with higher standards - Identify and tackle intrinsically hard process flow simulation problems (e.g., highly complex, ambiguous, undefined, with less existing structure, or having significant business risk or potential for significant impact - Deliver artifacts that set the standard in the organization for excellence, from process flow control algorithm design to validation to implementations to technical documents using simulations - Be a pragmatic problem solver by applying judgment and simulation experience to balance cross-organization trade-offs between competing interests and effectively influence, negotiate, and communicate with internal and external business partners, contractors and vendors for multiple simulation projects - Provide simulation data and measurements that influence the business strategy of an organization. Write effective white papers and artifacts while documenting your approach, simulation outcomes, recommendations, and arguments - Lead and actively participate in reviews of simulation data science solutions. You bring clarity to complexity, probe assumptions, illuminate pitfalls, and foster shared understanding within simulation data science discipline - Pay a significant role in the career development of others, actively mentoring and educating the larger simulation data science community on trends, technologies, and best practices - Use advanced statistical /simulation tools and develop codes (python or another object oriented language) for research , simulation, and modeling algorithms - Lead and coordinate simulation efforts between internal teams and outside vendors to develop optimal solutions for the network, including equipment specification, material flow control logic, process design, and site layout - Deliver results according to project schedules and quality A day in the life The day-to-day activities include challenging and problem solving scenario with fun filled environment working with talented and friendly team members. The stakeholders includes Worldwide Design Engineering org verticals, Fulfillment Technology and Robotics team members. The team solve problems related to critical design automation of Material handling equipment and technology design solutions. 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! About the team WWDE Simulation Team’s mission is to apply advanced simulation tools and techniques to drive process flow design, optimization, and improvement for the Amazon Fulfillment Network. We take ownership and pride to come up with simulation based solutions to drive the designs and earn the customer trust. We always strive to invent new ways to simulate and optimize the design and to invent design solutions. We help design and operation engineers to make simulation driven decisions by producing detailed math models and generating key performance metrics.

The Worldwide Design Engineering (WWDE) organization delivers innovative, effective and efficient engineering solutions that continually improve our customers’ experience. WWDE optimizes designs throughout the entire Amazon value chain providing overall fulfillment solutions from order receipt to last mile delivery. We are seeking a Simulation Scientist to assist in designing and optimizing the fulfillment network concepts and process improvement solutions using discrete event simulations for our World Wide Design Engineering Team. Successful candidates will be technical expert and natural self-starter who have the drive to apply simulation and optimization tools to solve complex flow and buffer challenges during the development of next generation fulfillment solutions. The Simulation Scientist is expected to deep dive into complex problems and drive relentlessly towards innovative solutions working with cross functional teams. Be comfortable interfacing and influencing various functional teams and individuals at all levels of the organization in order to be successful. Lead strategic modelling and simulation projects related to drive process design decisions. Key job responsibilities - You influence the scientific strategy across multiple teams in your business area. You support go/no-go decisions, build consensus, and assist leaders in making trade-offs. You proactively clarify ambiguous problems, scientific deficiencies, and where your team’s solutions may bottleneck innovation for other teams. - Lead the design, implementation, and delivery of the simulation data science solutions to perform system of systems discrete event simulations for significantly complex operational processes that have a long-term impact on a product, business, or function using FlexSim, Demo 3D, AnyLogic or any other Discrete Event Simulation (DES) software packages - Lead strategic modeling and simulation research projects to drive process design decisions - Be an exemplary practitioner in simulation science discipline to establish best practices and simplify problems to develop discrete event simulations faster with higher standards - Identify and tackle intrinsically hard process flow simulation problems (e.g., highly complex, ambiguous, undefined, with less existing structure, or having significant business risk or potential for significant impact - Deliver artifacts that set the standard in the organization for excellence, from process flow control algorithm design to validation to implementations to technical documents using simulations - Be a pragmatic problem solver by applying judgment and simulation experience to balance cross-organization trade-offs between competing interests and effectively influence, negotiate, and communicate with internal and external business partners, contractors and vendors for multiple simulation projects - Provide simulation data and measurements that influence the business strategy of an organization. Write effective white papers and artifacts while documenting your approach, simulation outcomes, recommendations, and arguments - Lead and actively participate in reviews of simulation research science solutions. You bring clarity to complexity, probe assumptions, illuminate pitfalls, and foster shared understanding within simulation data science discipline - Pay a significant role in the career development of others, actively mentoring and educating the larger simulation data science community on trends, technologies, and best practices - Use advanced statistical /simulation tools and develop codes (python or another object oriented language) for data analysis , simulation, and developing modeling algorithms - Lead and coordinate simulation efforts between internal teams and outside vendors to develop optimal solutions for the network, including equipment specification, material flow control logic, process design, and site layout - Deliver results according to project schedules and quality A day in the life The dat-to-day activities include challenging and problem solving scenario with fun filled environment working with talented and friendly team members. The internal stakeholders are IDEAS team members, WWDE design vertical and Global robotics team members. The team solve problems related to critical Capital decision making related to Material handling equipment and technology design solutions. 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! About the team World Wide Design EngineeringSimulation Team’s mission is to apply advanced simulation tools and techniques to drive process flow design, optimization, and improvement for the Amazon Fulfillment Network. Team develops flow and buffer system simulation, physics simulation, package dynamics simulation and emulation models for various Amazon network facilities, such as Fulfillment Centers (FC), Inbound Cross-Dock (IXD) locations, Sort Centers, Airhubs, Delivery Stations, and Air hubs/Gateways. These intricate simulation models serve as invaluable tools, effectively identifying process flow bottlenecks and optimizing throughput.

Twitch is looking for an Applied Scientist to lead computer vision and video manipulation work within Amazon Publisher Monetization (APM). You will apply large language models (LLMs), vision-language models (VLMs), and traditional computer vision techniques to build products that directly improve how millions of Twitch creators produce content and how viewers engage with it. This is a high-visibility project backed by senior leadership, and you will have the autonomy to evaluate both first-party and third-party solutions to deliver the highest quality results quickly. If you thrive in a fast-paced, startup-like environment where your scientific decisions shape the product roadmap, we want to hear from you. Key job responsibilities Design and deploy computer vision and video manipulation models using LLMs, VLMs, and traditional techniques, taking solutions from research prototype to production. Partner with senior Product and Twitch leadership to translate customer needs into well-defined scientific problems and deliver end-to-end solutions. Evaluate and integrate generative AI capabilities across Amazon Bedrock and third-party platforms, selecting the approach that maximizes product quality. Drive the team's scientific agenda by proposing new initiatives, authoring technical documents, and contributing to external publications. Mentor fellow scientists and engineers through code reviews, design guidance, and technical assessments that raise the overall quality bar. A day in the life You will split your time roughly evenly between independent research and collaborative sessions. Mornings often start with focused solo work — benchmarking a new VLM, writing model code, or analyzing experiment results. Midday you join working sessions with Product and Twitch leadership to align on requirements or review progress. Afternoons shift between pairing with engineers on production integration and mentoring teammates on evaluation methodology. Weekly science reviews and bi-weekly roadmap syncs keep the team aligned without over-scheduling your calendar. About the team The APM science team supports all of Amazon's Publisher Monetization efforts, building the models and systems behind Twitch's creator tools and ad experiences. The team includes applied scientists, software engineers, and product managers who collaborate daily to move ideas from whiteboard to production. We operate with a startup mentality — moving fast, wearing multiple hats, and iterating closely with Twitch and Product partners. We are accelerating investment in computer vision and generative AI, and this role will be central to that expansion.

Come be a part of a rapidly expanding $35 billion dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential. The Opportunity This is one of the most consequential science leadership roles in Amazon Business. As Applied Science Manager, you will directly influence over $40B in annual revenue by owning the science strategy that powers how we acquire, engage, monetize, and retain millions of business customers worldwide. Your models won't sit in notebooks. They will run in production, shaping real-time decisions across the full customer lifecycle for one of Amazon's fastest-growing businesses. You will operate at the intersection of Business Prime, Marketing Science, and Customer Acquisition three of the highest-visibility, highest-impact charters in the organization. Your work will be presented to VPs and SVPs, inform multi-billion-dollar investment decisions, and fundamentally reshape how Amazon Business goes to market. This is not an incremental optimization role. This is a build-the-future role where your science roadmap becomes the business strategy. What You'll Own Team Leadership & Talent Development: Build and lead a world-class team of applied scientists and research scientists. Set the technical vision, define the multi-year science roadmap, and create an environment where scientists ship models that move the needle on $40B+ in revenue. You will be the bar-raiser who attracts top talent and develops the next generation of science leaders at Amazon. Customer Lifecycle Intelligence ($40B+ Revenue Impact): Own the predictive modeling stack that powers customer identification, targeting, spend behavior forecasting, churn propensity, and declining engagement detection across every Business Prime segment. Your models will determine which customers we invest in, how we invest, and when directly impacting billions in customer lifetime value. Marketing Science & Measurement (Cross-Functional, Multi-Billion Dollar Allocation): Build the causal inference and attribution frameworks that determine how Amazon Business allocates hundreds of millions in marketing investment across paid, owned, and earned channels globally. You will be the single point of science truth for incrementality measurement, marketing mix modeling, and ROI optimization partnering with Marketing, Finance, CPS, and international teams to ensure every dollar drives maximum impact. Customer Acquisition Engine: Lead the science that accelerates new Business Prime member acquisition at scale. Build propensity models, audience optimization systems, and channel effectiveness frameworks that feed directly into acquisition engines serving 10+ global markets. Your work will be the difference between linear growth and exponential growth. Benefits Adoption & the "Aha Moment": Build behavioral segmentation and recommendation systems that identify, for each customer vertical and organizational profile, the exact moment and feature combination that converts a trialist into a loyalist. This is the science of delight at scale. Trust & Safety at Scale: Develop fraud detection models, abuse identification systems, and eligibility classifiers that protect the integrity of the Business Prime ecosystem safeguarding billions in revenue from bad actors. Experimentation & Causal Inference (Organization-Wide): Establish the experimentation frameworks and causal inference methodologies used across the entire Amazon Business organization. Design experiments that measure incremental impact of product launches, pricing changes, and marketing interventions creating the scientific foundation for how leadership makes high-stakes decisions. Why This Role Is Different This is not a role where you optimize a feature in isolation. You will sit at the center of a complex, cross-functional operating model partnering daily with 7+ senior leaders (including Directors and VPs) across Business Prime, CPS Sales, Central Marketing, SSR, GTMO, Finance, and International teams. Your science will be the connective tissue that aligns these organizations around a shared, data-driven growth strategy. You will have direct senior leadership visibility — presenting findings, recommendations, and roadmaps to VP audiences regularly. The insights your team generates will shape OP1/OP2 planning, Board-level narratives, and multi-year investment theses. What We're Looking For The successful Applied Science Manager will have an bias for action in a startup environment, with people leadership skills, a proven ability to build and manage high-performing science teams, define and prioritize research agendas that map to business outcomes, and build methodology and tools that are statistically grounded. You influence product and business strategy through science translating complex analytical findings into crisp, actionable recommendations that senior leaders act on immediately. We are seeking someone who thrives in a fast-paced, high-energy, and fun work environment where we deliver value incrementally and frequently. You are a highly technical leader who knows your subject matter deeply, can elevate the technical bar of your team, and is energized by ambiguity and new problem spaces. You know how to deliver results and show a desire to develop yourself, your colleagues, and your career.

Orchestrating the selection of one out of tens of millions of ads, honoring advertiser targeting intent for hundreds of thousands of advertisers while ensuring great shopper experience for billions of shoppers millions of times per second on a latency of tens of milliseconds is not a trivial task. The demand retrieval team within the Amazon DSP organisation deals with this challenge, developing and operating machine learning models that match ads opportunities with the most relevant ads to deliver the right messages to the right customers at the right time. We are looking for an Applied Scientist to optimize ad matching for Amazon’s programmatic advertisement products. In this role you will lead the design and implementation of solutions for performance sourcing, using behavioural information on customers’ interactions with Amazon and other owned and operated businesses as well as contextual information about the bid request to predict their propensity to convert, in turn driving better advertising campaign outcomes. Your work will affect multi-billion dollar businesses, and you will be responsible for designing, testing and delivering significant breakthrough's for Amazon's business. Successful candidates will have strong technical ability, excellent teamwork, communication skills, and a motivation to achieve business results in a fast-paced environment. Key job responsibilities * Design and implement deep learning models to match the right customers with the right ads across different verticals, geographies, and ads formats. * Investigate new ML techniques such as multi-task learning to ensure that models can operate for a variety of advertisers in multiple industries and with different volumes of conversion events. * Improve the performance, generalisation and scalability of models by introducing new features and enhancing models’ architecture. * Work side by side with our engineers to deliver code changes impacting our ads stack, working with very large datasets and high throughput production systems. * Rapidly prototype and test many possible hypotheses/implementation alternatives in a high-ambiguity environment, making use of both quantitative analysis and business judgement. * Be immersed in Amazon's advertisers and their objectives, and think long-term about how to turn those objectives into products and technical capabilities. * Understand the latest literature on machine learning for recommender and advertising systems, contributing to guiding strategic investment for the organization. A day in the life You will partner with our product and engineering teams, bringing your own ideas to the conversation and aligning on work, adjusting priorities based on business requirements and fast iteration on experiments. You will have a strong theoretical understanding of modern ML techniques and methodologies, and the software engineering and data processing skills to deploy these using the large-scale datasets we deal with in advertising. About the team The Demand Retrieval team is responsible for designing, implementing, deploying and operating machine learning models that match bid opportunities to ads demand based on performance, campaign delivery, and targeting objectives specified by advertisers. We measure the success of our approaches based on offline experimentation and and online metrics that measure the impact of our matching models on campaign KPIs (e.g.: cost per action, return on ads investment, budgets delivered, and targeting precision).

Our organization in Amazon Robotics builds robots that perform contact-rich manipulation safely and reliably in complex, unstructured environments, at Amazon scale. Our scientists and engineers push the boundaries of robotic manipulation to handle enormous object diversity, bringing deep expertise across planning, control, perception, and machine learning. We learn from real-world data at a scale that few teams in robotics can access. We are seeking an experienced Senior Applied Scientist to help guide a small team advancing reinforcement learning for manipulation. We are creating robots that learn how to push, flip, rearrange, and dexterously insert items with unparalleled robustness, speed, and reliability. Our goal is to deploy robots that will work across Amazon's global network and can handle the full diversity of items that Amazon sells. You will set the technical direction for how we learn these behaviors, from simulation training through reliable execution on physical robots, and you will demonstrate new manipulation capabilities on real hardware at scale. This team's mission reaches beyond any single product: to invent and apply manipulation capabilities that generalize to many future robotics applications. The robots our organization already deploys at scale give you a rare proving ground to collect data, run experiments, and get new policies onto real hardware faster than almost anywhere in the field. You will raise the bar for scientific rigor and engineering quality, and mentor other scientists as the team grows. Key job responsibilities - Set the technical direction for learning non-prehensile and contact-rich manipulation policies, from testing the latest advances in the field through demonstrated capability on hardware. - Oversee the development of reinforcement learning approaches that address the long tail of diverse, demanding manipulation conditions. - Own the path from simulation training to reliable, real-time execution on physical robots, making evidence based calls on where learned approaches should replace engineered ones. - Demonstrate new manipulation capabilities on real robots at scale, and turn one-off results into repeatable methods. - Establish the standards, evaluation practices, and data-informed improvement loops that the team builds on. - Mentor scientists and engineers, and raise the bar for applied science rigor and engineering quality. - Partner across control, perception, and hardware to integrate learned behaviors into working systems. - Represent Amazon in academia through publications and scientific presentations. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners. 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 seeking an Applied Scientist to build production machine learning systems that solve complex business problems at scale. You will design, develop, and deploy ML solutions that directly impact millions of users and drive strategic decision-making across the organization. In this role, you will work on challenging problems spanning predictive modeling, natural language processing, recommendation systems, and generative AI applications. You will collaborate with cross-functional teams to translate ambiguous business challenges into rigorous technical solutions. Key job responsibilities - Design and deploy large-scale machine learning systems in production environments - Develop innovative ML solutions using state-of-the-art techniques including deep learning, NLP, and generative AI - Create ML solutions that personalize manager on-boarding and development experiences — identifying individual capability gaps, recommending tailored learning pathways, and measuring development effectiveness across diverse manager populations and contexts - Partner to build causal inference models and experimental frameworks to measure impact - Collaborate with product managers, engineers, and business leaders to define technical roadmaps - Communicate complex technical concepts to diverse audiences, from technical peers to senior leadership About the team The People eXperience and Technology Central Science Team (PXTCS) uses economics, applied science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.

The Amazon Center for Quantum Computing (CQC) team is looking for a passionate, talented, and inventive Research Engineer specializing in hardware design for cryogenic environments. The ideal candidate should have expertise in 3D CAD (SolidWorks), thermal and structural FEA (Ansys/COMSOL), hardware design for cryogenic applications, design for manufacturing, and mechanical engineering principles. The candidate must have demonstrated experience driving designs through full product development cycles (requirements, conceptual design, detailed design, manufacturing, integration, and testing). Candidates must also have a strong background in both cryogenic mechanical engineering theory and implementation. Working effectively within a cross-functional team environment is critical. Key job responsibilities The CQC collaborates across teams and projects to offer state-of-the-art, cost-effective solutions for scaling the signal delivery to quantum processor systems at cryogenic temperatures. Equally important is the ability to scale the thermal performance and improve EMI mitigation of the cryogenic environment. You will work on the following: - High density novel packaging solutions for quantum processor units - Cryogenic mechanical design for novel cryogenic signal conditioning sub-assemblies - Cryogenic mechanical design for signal delivery systems - Simulation-driven designs (shielding, filtering, etc.) to reduce sources of EMI within the qubit environment. - Own end-to-end product development through requirements, design reports, design reviews, assembly/testing documentation, and final delivery A day in the life As you design and implement cryogenic hardware solutions, from requirements definition to deployment, you will also: - Participate in requirements, design, and test reviews and communicate with internal stakeholders - Work cross-functionally to help drive decisions using your unique technical background and skill set - Refine and define standards and processes for operational excellence - Work in a high-paced, startup-like environment where you are provided the resources to innovate quickly About the team The Amazon Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, on a mission to develop a fault-tolerant quantum computer. Inclusive Team Culture Here at Amazon, 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 conferences, inspire us to never stop embracing our uniqueness. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred 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. 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. Export Control Requirement Due to applicable export control laws and regulations, candidates must be either 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, or be able to obtain a US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.

AWS Global Sales drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched technology, and support. We dive deep to understand each customer's unique challenges, then craft innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud. Join us and help us grow. Are you a customer-obsessed builder passionate about helping enterprise customers achieve their full potential with Generative AI? Do you have deep data science expertise and the technical pre-sales acumen to help customers evaluate, design, and deploy GenAI and ML solutions on AWS? Do you enjoy building impactful AI agents and agentic applications? Join the GenAI/ML Specialist organization as a Senior Generative AI Data Scientist — a senior individual contributor role requiring deep data science expertise, hands-on ML engineering skills, and executive-level customer engagement. The AGS Specialist organization is part of the customer-facing NAMER sales organization, and is responsible for driving revenue and accelerating adoption of cloud and partner services across diverse customer segments. We work backwards from our customers' most complex and business-critical challenges to develop and execute go-to-market plans that transform ideas into scalable, high-impact businesses. AGS NAMER teams include sales specialists and technical solution architects. As part of the team, you will contribute across the full lifecycle of AWS customer initiatives—from shaping new service and solution concepts to accelerating adoption of established offerings. We pride ourselves on thinking big, delivering exceptional customer outcomes, and collaborating seamlessly across AWS as #OneTeam. Role Description In this role, you will be the Subject Matter Expert (SME) for helping NAMER Enterprise customers design and implement Generative AI solutions that leverage Amazon Bedrock. You will translate customer business challenges into data science-driven solutions using AWS. You will define, design, and deploy machine learning models, agentic workflows, and GenAI applications that accelerate adoption of AWS AI/ML services. You will engage with senior engineers, data scientists, product leaders, and executives at strategic enterprise customers to influence technical decisions and provide structured feedback to AWS product teams. You will interact with customers directly to understand their business problems, help and aid them in implementation of generative AI solutions, deliver briefings and deep dive sessions, and guide customers on adoption patterns and best practices for generative AI. You will build prototypes, proof-of-concepts, and explore novel solutions leveraging Amazon Bedrock, Amazon AgentCore, Strands Agents, and open source frameworks such as LangChain, LangGraph, and CrewAI. This position will focus on agentic workflows with Amazon Bedrock, including Strands Agents, Bedrock Agents, and open source agentic frameworks. You must have deep technical experience working with technologies related to large language models including LLM architectures, model evaluation, and fine-tuning techniques. You should be proficient with design, deployment, and evaluation of LLM-powered agents, tools, and orchestration approaches. You will interface with customer data science teams, ML engineering leadership, and C-suite executives to advise on the latest techniques, model architectures, and emerging research. This includes staying current with state-of-the-art approaches from recent publications and research papers — such as advances in reasoning models, multi-agent systems, retrieval-augmented generation, reinforcement learning from human feedback (RLHF), and novel fine-tuning methods — and translating those findings into practical, production-ready solutions for enterprise customers. You will lead technical deep dives and whiteboard sessions with customer chief data scientists and VPs of AI/ML, bridging the gap between research and real-world implementation on AWS. You should understand the security and compliance requirements for ML/GenAI implementations. You should have experience architecting end-to-end ML/GenAI agentic applications for customers using AWS services and the Well-Architected Framework. As the ideal candidate, you bring a deep data science background and the business acumen required to lead complex engagements with large enterprises. You have hands-on expertise in statistical modeling, traditional ML, and current areas such as LLMs, RAG, fine-tuning, AI system evaluation, prompt engineering, agents, and AIOps. You are able to credibly advise senior technical and executive stakeholders on architectural trade-offs, best practices, and risk mitigation. Key job responsibilities - Working with NAMER Enterprise customers' development and data science teams to deeply understand their business and technical needs. Design and implement solutions that make the best use of the AWS cloud platform and AWS AI/ML services including SageMaker, Amazon Bedrock, Amazon AgentCore, and other AI/ML services. - Customer Advisor — Implement and deploy state-of-the-art machine learning and Generative AI solutions. Build prototypes, PoCs, and explore new solutions. Interact closely with enterprise customers to accelerate their AI/ML adoption. - Partner with Data Scientists, SAs, Sales, Business Development, and the AI/ML Service teams to accelerate customer adoption and revenue attainment in NAMER for Amazon Bedrock, SageMaker, and related services that support GenAI use cases. - Thought Leadership – Evangelize AWS GenAI services and share best practices through forums such as AWS blogs, whitepapers, reference architectures, and public-speaking events such as AWS Summit, AWS re:Invent, etc. - Act as a technical liaison between customers and the Amazon Bedrock or other service teams to provide customer-driven product improvement feedback. - Develop and support an AWS internal community of GenAI-related subject matter experts in the AMERICAS. Create field enablement materials for the broader technical population, to help them understand how to integrate AWS GenAI solutions into customer architectures. A day in the life Your day will be dynamic and impactful. You'll engage with enterprise business leaders, dive deep into ML architectures and data science pipelines, and craft transformative AI strategies. You'll collaborate across teams, translating complex statistical and AI concepts into clear, actionable solutions that drive meaningful business outcomes for NAMER Enterprise customers. About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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.