Careers

Amazon is the 4th most popular site in the US. Our product search engine, one of the most heavily used services in the world, indexes billions of products and serves hundreds of millions of customers world-wide. The Search Query Understanding team is at the forefront of revolutionizing the online shopping experience through the Amazon search page. Our ambition is to transform the search engine into a shopping engine. Leveraging advances in Large Language Models (LLMs), we aim to deeply understanding our users' shopping missions, preferences, and goals. By developing responsive and scalable solutions, we not only accomplish the shopping mission but also foster unparalleled trust among our customers. Through our advanced technology, we generate valuable insights, ensuring a comprehensive and holistic shopping experience. Our dedication to continuous improvement through constant measurement and enhancement of the shopper experience is crucial, as we strategically navigate the balance between immediate results and long-term business growth. We are seeking an Applied Scientist who is not just adept in the theoretical aspects of Machine Learning (ML), Artificial Intelligence (AI), and Large Language Models (LLMs) but also possesses a pragmatic, hands-on approach to navigating the complexities of innovation. The ideal candidate should have a profound expertise in one or more areas including but not limited to Retrieval Augmented Generation (RAG), post-training of foundation models and LLM inference optimizations. You will take the lead in conceptualizing, building, and launching innovative models that significantly improve our understanding of search missions and capabilities in enhancing the search experience. A successful applicant will display a comprehensive skill set across machine learning model development, implementation, and optimization. This includes a strong foundation in data management, software engineering best practices, and awareness of the latest developments in model lifecycle management. We are looking for individuals who are analytically rigorous, passionate about applied sciences, creative, and possess strong logical reasoning abilities. Join the Search Query Understanding team, a group of pioneering ML scientists and engineers dedicated to building core ML models and developing the infrastructure for model innovation. As part of Amazon Search, you will experience the dynamic, innovative culture of a startup, backed by the extensive resources of Amazon.com (AMZN), a global leader in internet services. Our collaborative, customer-centric work environment spans across our offices in Palo Alto, CA, and Seattle, WA, offering a unique blend of opportunities for professional growth and innovation. Key job responsibilities Collaborate with cross-functional teams to identify requirements for ML model development, focusing on enhancing mission understanding through innovative AI techniques, including retrieval-Augmented Generation or LLM in general. Design and implement scalable ML models capable of processing and analyzing large datasets to improve search and shopping experiences. Must have a strong background in machine learning, AI, or computational sciences. Lead the management and experiments of ML models at scale, applying advanced ML techniques to optimize science solution. Serve as a technical lead and liaison for ML projects, facilitating collaboration across teams and addressing technical challenges. Requires strong leadership and communication skills, with a PhD in Computer Science, Machine Learning, or a related field.

Define the joint optimization of model compression and silicon architecture for Amazon's next generation of edge and cloud inference accelerators. Your work will set the technical targets that propagate across the model, compiler, runtime, and silicon stack. We are hiring a Sr. Applied Scientist to be the technical leader who closes the loop between compression science and silicon design. Today's generation ships advanced quantization and large-model distillation in production, running multi-billion parameter language models at inference economics typical of much larger systems. Future generations target significantly larger models at the edge and in the cloud. You will be a senior architect of the next-generation accelerator and of the compression algorithms it executes natively. Few roles in the industry let one technical leader influence the model, the compiler, the runtime, and the silicon without organizational friction. This is one of them. You have spent the last several years thinking about why hardware decisions and accuracy decisions live in different teams, and you want to be the person who owns both. You have published at MLSys, ISCA, MICRO, NeurIPS, or ICML on quantization, pruning, or hardware-aware training, and you want your next paper to ship in a chip rather than in a benchmark suite. You want a vertical stack—model, compression, compiler, runtime, operating system, silicon—where the same engineering organization owns every layer and a sr. architect can move all of them. Key job responsibilities • Define the hardware-aware compression roadmap for next-generation accelerators, working backward from accuracy targets on standard language and reasoning benchmarks including Massive Multitask Language Understanding (MMLU), GSM8K, HumanEval, and Instruction Following Evaluation (IFEval). • Own the joint optimization of compression algorithms (post-training quantization, quantization-aware training, knowledge distillation, structured pruning) with the underlying hardware. • Represent applied science in silicon architecture reviews and influence decisions across the memory and compute subsystems of the accelerator. • Set the science roadmap for the compression techniques the next architecture must support; validate that compression algorithms achieve target accuracy on the benchmarks our products are evaluated against. • Mentor a team of senior and mid-level applied scientists working on compression and hardware-aware training. • Serve as a single-threaded technical leader for the codesign agenda, accountable to senior leadership review. About the team Amazon's Devices and Services organization has shipped multiple generations of first-party silicon for consumer devices. The differentiating intellectual property across this portfolio is a custom machine learning processor co-designed with the compression algorithms it runs. This role sits at the intersection of three teams. The Applied Science team produces compressed model checkpoints. The Silicon Engineering team designs the Application-Specific Integrated Circuits (ASICs). The Compiler and Runtime team lowers compressed models to silicon. You will be the Sr. architect who closes the loop across all three.

The Alexa International Science team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong background in speech models (understanding and generation) and deep learning, to help build industry-leading Generative AI technology with speech-to-speech models and multilingual systems. At this level, you will drive cross-team scientific strategy for speech quality across international locales, influence partner teams, and deliver solutions that have broad impact across Alexa's global products. Key job responsibilities As a Senior Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in multilingual speech generation, text-to-speech synthesis, and speech-to-speech models. Your work will directly impact customers across multiple languages in the form of natural, expressive, and locale-appropriate voice experiences for Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in speech synthesis, voice quality, and pronunciation accuracy for non-English locales. The ideal candidate possesses a solid understanding of machine learning, speech synthesis (TTS/S2S), multilingual phonetics, modern model architectures, and evaluation methodology. They thrive in a fast-paced environment, tackle complex challenges in low-resource language settings, excel at delivering impactful solutions while iterating based on customer feedback, and are able to influence and align multiple teams around a shared scientific vision for international speech quality. A day in the life You will start your day reviewing experiment results and iterating on model architectures for speech generation. You will collaborate with software engineers to optimize model performance for production deployment, and partner with product managers to align research priorities with customer needs. You will participate in science reviews, paper reading groups, and brainstorming sessions with fellow scientists across the organization. Your work directly impacts how Alexa sounds and communicates with customers in international markets, making every day an opportunity to solve meaningful problems at global scale. About the team The Alexa International Tech team helps Alexa' global expansion scalable, reliable, and locally relevant for customers. We build the science, engineering, evaluation, and quality platforms behind global AI product delivery: multi-model AI orchestration, multilingual model and data readiness, speech and language quality, reward modeling, synthetic data generation, automated evaluation, developer tooling, defect analysis, and launch mechanisms. Our work sits at the intersection of applied AI, speech, distributed systems, developer experience, and customer quality automation. The goal is simple but hard: help teams build Alexa+ experiences once and scale them across languages, countries, devices, models, and customer expectations without reinventing the same mechanisms every time.

Are you a scientist interested in pushing the state of the art in machine learning and recommendation systems? Are you interested in working on novel ideas that can positively impact millions of customers? Do you wish you had access to large datasets and tremendous computational resources? Answer yes to any of these questions and you will be a great fit for our team at Amazon. As an Applied Scientist in our team, you will be responsible for the research, design, and development of new AI technologies for Personalization. You will adopt or invent new machine learning and analytical techniques in the realm of recommendations and large language models. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include inventing, experimenting with, and launching new features, products and systems. Key job responsibilities - Using Amazon’s large-scale computing resources, you will ask research questions about customer behavior, build state-of-the-art models to optimize the shopping experience, and run these models directly on the retail website. - Develop AI solutions for Recommendation systems using Deep learning, LLMs, Reinforcement Learning, distillation, and Optimization methods; - Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; - Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses; - Effectively communicate technical and non-technical ideas with teammates and stakeholders; - Stay up-to-date with advancements and the latest modeling techniques in the field; - Publish your research findings in top conferences and journals. About the team Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. We run global experiments and our work has revolutionized e-commerce with features such as "Keep shopping for ...", “Customers who bought this item also bought”, and “Frequently bought together”.

The Alexa International Science team is looking for a passionate, talented, and inventive Applied Science Manager with a strong background in speech models (understanding and generation) and deep learning, to lead a team building industry-leading Generative AI technology with speech-to-speech models and multilingual systems. You will lead a team of Applied Scientists, drive cross-team scientific strategy for speech quality across international locales, influence partner teams, and deliver solutions with broad impact across Alexa's global products. You will own programs with global visibility and interact with a cross-functional group of Science, Product, and Engineering leaders. Your team's work will advance the state of the art in multilingual speech generation, text-to-speech synthesis, and speech-to-speech models, directly impacting customers across 20+ languages with natural, expressive, and locale-appropriate voice experiences for Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in speech synthesis, voice quality, and pronunciation accuracy for non-English locales. The ideal candidate possesses a solid understanding of machine learning, speech synthesis (TTS/S2S), multilingual phonetics, modern model architectures, and evaluation methodology. They thrive in a fast-paced environment, tackle complex challenges in low-resource language settings, and are able to influence and align multiple teams around a shared scientific vision. Core Leadership and Team Management - Lead and manage applied scientists focused on multilingual speech generation and voice personality - Build and develop high-performing science teams focused on speech synthesis, pronunciation, evaluation, and multilingual model adaptation - Set technical direction and raise the bar on scientific rigor, experimental methodology, and publication quality - Hire, mentor, and grow scientists at multiple levels Cross-Organizational Collaboration - Partner with cross org stakeholders to align goals and accelerate delivery - Establish clear communication channels and workflows across organizational boundaries - Drive alignment between science roadmaps and product launch timelines across 20+ locales Delivery and Execution - Own end-to-end delivery of speech quality improvements from research through production deployment - Define success metrics and evaluation frameworks for multilingual speech quality - Balance long-term research investments with near-term launch commitments Key job responsibilities * Lead and manage a team of Applied and Data scientists responsible for building and enhancing capabilities for Alexa+ * Collaborate with cross-functional teams to build methods to align Amazon’s LLMs with human preferences. * Identify and prioritize research opportunities that have the potential to significantly impact our AI systems. * Mentor and guide team members to achieve their career goals and objectives. * Communicate research findings and progress to senior leadership and stakeholders. * Rapidly experiment and drive productisation to deliver customer impact. * Drive academic partnership with top tier Indian university as part of the org’s AI/ML Center initiative. * Participate in and drive science publications in peer-reviewed venues of repute. About the team The Alexa International Science team drives multilingual AI quality for Alexa+, ensuring customers across all supported languages receive a natural, accurate, and culturally appropriate voice experience. We work at the intersection of speech science, LLMs, and international product launches.

The Alexa International Science team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong background in speech models (understanding and generation) and deep learning, to help build industry-leading Generative AI technology with speech-to-speech models and multilingual systems. At this level, you will drive cross-team scientific strategy for speech quality across international locales, influence partner teams, and deliver solutions that have broad impact across Alexa's global products. Key job responsibilities As a Senior Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in multilingual speech generation, text-to-speech synthesis, and speech-to-speech models. Your work will directly impact customers across multiple languages in the form of natural, expressive, and locale-appropriate voice experiences for Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in speech synthesis, voice quality, and pronunciation accuracy for non-English locales. The ideal candidate possesses a solid understanding of machine learning, speech synthesis (TTS/S2S), multilingual phonetics, modern model architectures, and evaluation methodology. They thrive in a fast-paced environment, tackle complex challenges in low-resource language settings, excel at delivering impactful solutions while iterating based on customer feedback, and are able to influence and align multiple teams around a shared scientific vision for international speech quality. A day in the life You will start your day reviewing experiment results and iterating on model architectures for speech generation. You will collaborate with software engineers to optimize model performance for production deployment, and partner with product managers to align research priorities with customer needs. You will participate in science reviews, paper reading groups, and brainstorming sessions with fellow scientists across the organization. Your work directly impacts how Alexa sounds and communicates with customers in international markets, making every day an opportunity to solve meaningful problems at global scale. About the team The Alexa International Tech team helps Alexa+ global expansion scalable, reliable, and locally relevant for customers. We build the science, engineering, evaluation, and quality platforms behind global AI product delivery: multi-model AI orchestration, multilingual model and data readiness, speech and language quality, reward modeling, synthetic data generation, automated evaluation, developer tooling, defect analysis, and launch mechanisms. Our work sits at the intersection of applied AI, speech, distributed systems, developer experience, and customer quality automation. The goal is simple but hard: help teams build Alexa+ experiences once and scale them across languages, countries, devices, models, and customer expectations without reinventing the same mechanisms every time.

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video subscriptions such as Apple TV+, HBO Max, Peacock, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities As a highly experienced and seasoned science leader, you will apply state of the art natural language processing and computer vision research to video centric digital media, while also responsible for creating and maintaining the best environment for applied science in order to recruit, retain and develop top talent. You will lead the research direction for a team of deeply talented applied scientists, creating the roadmaps for forward-looking research and communicate them effectively to senior leadership. You will also hire and develop applied scientists - growing the team to meet the evolving needs of our customers. About the team This team's mission is to deeply understand all content and empower all customers with relevant language options, innovative accessibility assists, and rich title-information across all their content-experiences on Prime Video. We create and publish content on-time that's meaningful, accurate, and accessible to every customer globally. We delight our customers by pushing the boundaries of content understanding and enrichment. Through inclusion and innovation, we do the most fulfilling work of our career.

We are seeking a scientist with deep programmatic and Ads experience to further the development and application of analytics methods to examine the complex data flows of the entre Amazon Ads system, and to translate deep-dives into actionable insights for our product teams. In this role you will develop new tools to analyze our advertising data to help improve the performance of our bidding algorithms, targeting and relevance systems, help advance our 3rd party and O&O supply strategy, and evaluate the adoption and impact of feature releases. Key job responsibilities • Analyze data trends regarding supply, optimization, ad load, and advertising mix effects that affect advertiser performance and contribute to achieving advertiser goals. • Present papers to senior leaders on issues like feature development impact on identity recognition rates, and changes of ad selection systems to improve fill rate highlighting insights that will inform our business development and engineering roadmaps. • Formalize our analytics approach to the DSP auctions by analyzing bid spreads, auction depth, and simulating impacts of potential auction structure changes. • Identify, standardize, and operationalize KPIs to effectively measure the performance of all systems involved in ad serving, and use trend insights to inform business priorities. • Partner with engineering teams to define data logging requirements and getting these prioritized in engineering roadmaps. • Validate financial models through analysis. • Develop and own ad revenue and supply intelligence analytics decks that provide ongoing deep-dives. A day in the life The DSP Analytics Leader will work closely with business leaders and engineers on developing common data architecture that will optimize our data logging at different grains, and will allow data interoperability from bid flow to optimization to campaign delivery. The candidate will then analyze the data and present papers and ongoing reports on actionable insights. About the team The DSP Ads Product Analytics Team's Mission: Work alongside those who need product data to apply objective perspective and business logic to uncover insights, advise strategic decisions, and adjust to industry changes.

Employer: Amazon Web Services, Inc. Position: Data Scientist II Location: Mountain View, CA Multiple Positions Available: Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production. (40 hours / week, 8:00am-5:00pm, Salary Range $157300 - $212800) Amazon.com is an Equal Opportunity – Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation

We are seeking an Applied Scientist to join Amazon Robotics, Compass Team. In this role, you will own the development of safe legged locomotion algorithms and their deployment on physical hardware, developing learning-based controllers that enable quadrupeds and humanoids to walk, run, and recover from disturbances with agility and robustness. You will leverage Reinforcement Learning (RL), sim-to-real transfer, and other learning-based architectures to train policies that produce stable, dynamic gaits across varied terrains and operating conditions. These learned policies will interface with model-based control strategies to form whole-body control laws that balance performance and safety. Your work sits at the novel intersection of safety and machine learning, where these learned policies will be used in a safety-critical context for complex safety constraints like stability. You will collaborate closely with perception, planning, and safety teams to close the loop between what the robot sees, where it needs to go, and how it moves to get there safely. This is a rare opportunity to shape how legged robots move through the world alongside people. Key job responsibilities • Design, train, and deploy reinforcement learning policies for dynamic legged locomotion including walking, running, stair climbing, and fall recovery on physical quadruped and humanoid platforms • Collaborate with the Compass safety team to ensure locomotion policies operate within safety-critical bounds, incorporating control barrier functions or other formal safety mechanisms as constraints during or after training • Develop sim-to-real transfer pipelines that produce policies robust to the reality gap, including domain randomization, system identification, and adaptive strategies • Integrate learned locomotion policies with model-based whole-body controllers, defining how RL outputs (e.g., joint targets, contact schedules) interface with optimization-based control layers • Formulate reward functions and training curricula that encode both performance objectives and safety constraints, ensuring policies respect stability and contact-force limits • Develop and maintain large-scale training infrastructure for locomotion policy learning, including physics simulation environments and parallelized training pipelines • Evaluate policy performance rigorously through simulation benchmarks, hardware experiments, and failure-mode analysis • Investigate emerging techniques (e.g., foundation models for control, diffusion policies, world models) and assess their applicability to safe legged locomotion • Publish research at top-tier robotics and ML venues and contribute to Amazon's scientific reputation in legged robotics • Collaborate with perception and planning teams to enable terrain-aware and goal-conditioned locomotion behaviors A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team Work with the inventors of control barrier functions on a novel, universal approach to safe autonomy: one that scales across mobile robots, manipulators, mobile manipulators, and future robot platforms with dynamic stability. You'll push the boundary of safe performance by integrating safety with motion planning, RL, and foundation models, ensuring that safety is never a blocker to robot performance. Your work will underpin robots operating alongside people at Amazon's unprecendented scale.