Careers

Amazon AGI Lab is a frontier research and product team combining the speed of a startup with Amazon’s scale and resources. We build agents that can perceive, reason, and take action to complete real-world tasks. The lab is designed to empower AI researchers and engineers to make major breakthroughs with speed and focus toward this goal. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We're hiring a principal engineer who can take models from prototype to production and build the systems that make them run reliably at scale. The bar is end-to-end ownership: your work can range from working alongside researchers to build novel architectures, to being the person who decides what the agent runtime looks like, where the data lives, and how we know it's delivering value. Key job responsibilities - Set the technical direction for the team - Partner closely with researchers to take emerging VLM and agent ideas from prototype to robust, instrumented systems that can be evaluated, improved, and scaled - Create tooling that accelerates research and engineering velocity - Raise the engineering bar for the team through technical design reviews, mentoring, principled architecture, high-quality code, observability, and operational excellence - Influence the broader AGI organization by identifying reusable primitives, writing clear technical strategy, and creating systems that other teams can build on - Be a thought leader & represent the lab externally by sharing ideas through thoughtful writing, conference talks, research publications, and open-source contributions, helping advance the field while raising the visibility and impact of the team’s work

The Amazon Devices & Services Demand Science (DSci) team is seeking a scientist with strong and AI/ML and communication skills to help with demand forecasting and supply optimization for the entire Amazon device family of products, services, and accessories. Amazon Devices represents a highly complex space with 100+ products across several product categories (e-readers [Kindle], tablets [Fire Tablets], TV [Fire TV and remote], smart speakers and audio assistants [Echo], wifi routers [eero], and video doorbells and cameras [Ring and Blink]), for sales both online and in offline retailers globally. We develop scalable and robust state-of-the-art ML, AI, and automation solutions — including transformer-based forecasting architectures, large language model (LLM)-powered agents, and agentic AI workflows — that learn from diverse data sources and power advanced predictive models. With better forecasts we drive down supply chain costs, enabling the offer of lower prices and better in-stock selection for our customers. In this role, you will own the full lifecycle — from research through production deployment. You will drive end-to-end solutions: understanding business requirements, exploring large-scale historical data and ML models, building prototypes, developing conceptually new approaches (including AI-native experimentation and agent-driven automation), and partnering with engineering teams to deploy and maintain solutions in production. You will collaborate closely with scientists, engineering peers, and business stakeholders. You will be at the heart of a growing and exciting focus area for Amazon Devices and Services where AI is transforming how we forecast, validate, and optimize decisions. You are an individual with strong science abilities, excellent communication skills, solid coding skills, and comfort with modern AI tools and frameworks. You will be responsible for researching, prototyping, experimenting, analyzing predictive models, implementing production-ready solutions, and developing AI-driven automation that progressively reduces manual intervention and enables hands-off-the-wheel science operations. Key job responsibilities - Build forecasting models from prototype through production, working closely with engineering to deploy at scale - Find and integrate new data sources to improve forecast accuracy and coverage - Design and deliver production-ready solutions for business-critical forecasting and optimization problems - Define and track performance metrics — both technical (error rates, bias, coverage) and business (plan attainment, financial impact, reduction in manual overrides) - Write and maintain clear technical documentation; present findings and recommendations to scientists, engineers, and business leaders - Set team standards for methodology, code quality, experimentation rigor, and AI-assisted workflows About the team We are a focused science team looking for help with enhancing the demand forecasting framework we're building and figuring out how to best solve the needs of both our internal stakeholders and cross-functional partners.

As part of the AWS Applied AI Solutions organization, we're building the future of AI-powered enterprise services across multiple domains. Our vision is to be the trusted foundation for transforming every business with Amazon AI teammates. Our mission is to deliver turnkey, enterprise-grade foundational AI capabilities that create delightful AI powered solutions. We're developing sophisticated AI systems that address complex challenges across autonomous operations, geospatial intelligence, trust and safety, IoT services, and foundational AI platforms. Key job responsibilities * Develop and productize AI solutions that address complex technical challenges requiring novel approaches beyond off-the-shelf tools * Design and implement machine learning systems for diverse applications including video understanding, geospatial optimization, fraud detection, anomaly detection, and automation * Create scalable algorithms and models that generalize across multiple customer use cases and business problems * Conduct rigorous experimentation with state-of-the-art techniques including large language models, computer vision, federated learning, or physics-based modeling, and agentic AI systems * Collaborate with engineering teams to integrate science components into production systems with measurable customer impact * Work directly with product teams to understand requirements, frame ambiguous problems into tractable science solutions, and validate approaches through proof of concepts * Establish evaluation frameworks and best practices for measuring solution performance and business impact * Mentor other scientists and contribute to the broader scientific community through publications when appropriate A day in the life As an Applied Scientist, you'll work on challenging problems that span multiple domains within AWS Core Services. You might develop video processing architectures for autonomous systems, create optimization solvers for geospatial applications, build behavioral detection models for fraud prevention, design anomaly detection systems for IoT devices, or develop specialized AI capabilities for platform services. You'll investigate novel approaches, validate ideas through rigorous experimentation with real data, and collaborate with scientists and engineers to transform research insights into scalable solutions. About the team Our team is a central science organization supporting multiple product teams across AWS Core Services. We tackle fundamental challenges in AI and machine learning that require novel approaches beyond off-the-shelf solutions. Working at the intersection of machine learning, large language models, and domain-specific applications, we develop practical techniques that advance the state-of-the-art while maintaining a clear path to customer impact. Our team builds deep domain expertise across geospatial intelligence, trust and safety systems, autonomous operations, and other critical areas, collaborating closely with engineering teams to transform research insights into scalable production solutions.

Applied Scientists in AWS Science of Security are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for security, privacy, and sovereignty. Key job responsibilities The successful candidate will: * Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. * Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. *Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. * Develop strategic plans to identify fundamentally new solutions for business problems. * Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team 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.

We are seeking an Applied Scientist to join the Amazon Precision Match (APM) team within Customer Journey, Network Solutions. APM is a transformative initiative replacing Amazon's legacy queue-based customer service routing with intelligent algorithmic matching — connecting customers with the best available service option based on their needs and Customer Service Associates (CSA) capabilities. This role will drive the science behind a high-scale system with significant projected impact on operational efficiency and customer experience. You will work at the intersection of recommendation systems, real-time ML inference, and large-scale experimentation to redefine how Amazon serves its customers. Key job responsibilities - Design, develop, and optimize ML-based matching algorithms that pair customers with optimal CSAs based on contact complexity, intent, and CSA skill profiles. - Build and iterate on feature engineering pipelines across CSA-level (skills, tenure, sentiment handling), contact-level (intent, complexity, urgency), and customer-level (language, communication style) attributes. - Run offline simulations on large-scale historical contact data and design statistically rigorous A/B experiments to validate matching improvements. - Develop real-time low-latency scoring and inference systems for production contact routing. - Address the cold start problem for new CSAs and build continuous model retraining infrastructure using production feedback. - Partner with CS Economics, Capacity Planning, and Quality teams on experiment design and results interpretation. - Evolve the matching framework from individual CSA ranking to set-based optimization balancing performance and operational sustainability. A day in the life You will spend your days iterating on matching models, analyzing experiment results from live production traffic, and collaborating with engineers and product managers to translate science insights into system improvements. You'll partner with the Customer Service Economics team to design experiments, review simulation outputs, and present findings to senior leadership. You'll also deep-dive into CSA behavioral patterns, contact transcripts, and performance data to identify new matching signals and continuously improve the algorithm. About the team The Amazon Precision Match team is a high-impact, fast-moving science and engineering team within Customer Journey, Network Solutions. Our mission is to ensure every Amazon customer is connected with the right service option at the right time — improving customer experience while driving operational efficiency at scale. We value intellectual curiosity, rigorous experimentation, and a bias for action. We operate with a continuous improvement flywheel: offline simulation, A/B testing, and production rollout. We collaborate closely with Customer Service Operations, Capacity Planning, Quality, and partner science teams across Amazon.

Our team is involved with pre-silicon design verification for custom IP. A critical requirement of the verification flow is the requirement of legal and realistic stimulus of a custom Machine Learning Accelerator Chip. Content creation is built using formal methods that model legal behavior of the design and then solving the problem to create the specific assembly tests. The entire frame work for creating these custom tests is developed using a SMT solver and custom software code to guide the solution space into templated scenarios. This highly visible and innovative role requires the design of this solving framework and collaborating with design verification engineers, hardware architects and designers to ensure that interesting content can be created for the projects needs. Key job responsibilities Develop an understanding for a custom machine learning instruction set architecture. Model correctness of instruction streams using first order logic. Create custom API's to allow control over scheduling and randomness. Deploy algorithms to ensure concurrent code is safely constructed. Create coverage metrics to ensure solution space coverage. Use novel methods like machine learning to automate content creation. About the team Utility Computing (UC) 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, including support for customers who require specialized security solutions for customers who require specialized security solutions for their cloud services. Annapurna Labs (our organization within AWS UC) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.

Amazon's Pricing Science is seeking a driven Applied Scientist to harness planet scale multi-modal datasets, and navigate a continuously evolving competitor landscape, in order to regularly generate fresh customer-relevant prices on billions of Amazon products worldwide. We are looking for a talented, organized, and customer-focused applied researchers to join our Pricing Optimization science group, with a charter to measure, refine, and launch customer-obsessed improvements to our pricing algorithms across all products listed on Amazon. This role requires an individual with exceptional machine learning and predictive modeling skills, causal and experimental evaluation experience, excellent cross-functional collaboration skills and business acumen, and an entrepreneurial spirit. We are looking for an experienced innovator, who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work independently to deliver business impact. Key job responsibilities - See the big picture. Understand and develop science to influence the long term vision for Amazon's science-based competitive, perception-preserving pricing techniques - Build strong collaborations. Partner with product, engineering, and data teams within Pricing & Promotions to deploy models at Amazon scale - Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in machine learning, reinforcement learning, causal ML, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing & Promotions business problems - Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery. - Successfully execute & deliver. Apply your exceptional technical machine learning expertise to incrementally move the needle on some of our hardest pricing problems. A day in the life We are hiring an applied scientist to drive our pricing optimization initiatives. The Price Optimization science team drives cross-domain and cross-system improvements through: - Invent and deliver price optimization, simulation, and competitiveness tools for Sellers. - Promotion optimization initiatives exploring CX, discount amount, and cross-product optimization opportunities. - Identifying opportunities to optimally price across systems and contexts (marketplaces, request types, event periods) Price is a highly relevant input into many partner-team architectures, and is highly relevant to the customer, therefore this role creates the opportunity to drive extremely large impact (measured in Bs not Ms), but demands careful thought and clear communication. About the team About the team: the Pricing Optimization team within P2 Science owns price quality, discovery and discount optimization initiatives, including criteria for internal price matching, price discovery into search, p13N and SP, pricing bandits, and Promotion type optimization. We leverage planet scale data on billions of Amazon and external competitor products to build advanced optimization models for pricing, elasticity estimation, product substitutability, and optimization. We preserve long term customer trust by ensuring Amazon's prices are always competitive and error free.

Are you excited about leveraging and extending state-of-the-art Deep Learning, Information Retrieval, Natural Language Processing, Computer Vision algorithms to solve customer problems at the scale of Amazon? As an Applied Scientist Intern, you will be working in the Melbourne office in a fast-paced, cross-disciplinary team of experienced R&D scientists. You will take on complex problems, work on solutions that leverage existing academic and industrial research, and utilize your own out-of-the-box pragmatic thinking. In addition to coming up with novel solutions and prototypes, you may even deliver these to production in customer facing products. Key job responsibilities - Develop novel solutions and build prototypes - Work on complex problems in Deep Learning and Generative AI - Contribute to research that could significantly impact Amazon operations - Collaborate with a diverse team of experts in a fast-paced environment - Present your research findings to both technical and non-technical audiences - Collaborate with scientists on writing and submitting papers to top ML conferences, e.g. NeurIPS, ICML, ICLR, AISTATS, ACL ICCV, CVPR, KDD. Key Opportunities: - Work in a team of ML scientists to solve applied science problems at the scale of Amazon - Access to Amazon services and hardware - Potentially deliver solutions to production in customer-facing applications - Opportunities to be hired full-time after the internship Join us in shaping the future of AI at Amazon. Apply now and turn your research into real-world solutions!

Are you inspired by invention? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Last Mile Simulations and Analytics Engineering team. WW AMZL Simulations and Analytics Engineering team is looking to build out our Simulation team to drive innovation across our Last Mile network. We start with the customer and work backwards in everything we do. If you’re interested in joining a rapidly growing team working to build a unique, solutions advisory group with a relentless focus on the customer, you’ve come to the right place. This is a blue-sky role that gives you a chance to roll up your sleeves and dive into big data sets in order to build discrete event 3D simulations using tools like Flexsim, Anylogic, Emulate 3D etc and experimentation systems at scale, build optimization algorithms and leverage advanced technologies across Amazon. This is an opportunity to think big about how to solve a challenging problem for the customers. As a Sr. Simulation Scientist, you are 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. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future. You will apply advanced designs and methodologies for complex use cases across Last Mile network to drive innovation. In addition, you will contribute to the end state vision for simulation and experimentation of future delivery stations at Amazon. Key job responsibilities • 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 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!

Applied Scientists in AWS Science of Security are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for security, privacy, and sovereignty. Key job responsibilities The successful candidate will: * Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. * Own the design, implementation, and delivery for solutions that have a long-term quantifiable impact. *Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. * Develop fundamentally new solutions for business problems. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team 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.