Careers

Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more, all with the shared goal of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments, and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems. Key job responsibilities The Applied Scientist serves as key contributor supporting recruiting program managers, recruiters, and AUTA leadership while providing technical guidance to demand planning, school strategy, and supply forecasting teams. • Own science models that power target school recommendations, talent supply projections, and school-to-requisition matching across Amazon's global campus recruiting footprint. • Create data-driven models that optimize school sourcing strategies and recruiter decision-making while considering diversity requirements, data privacy thresholds, and institution-specific characteristics. • Develop and maintain supply forecasting models, school ranking algorithms, and multi-objective optimization systems using time-series forecasting, machine learning, survival analysis, and causal inference techniques. • Lead development of AI systems to automate school identification, supply-demand gap analysis, and strategy recommendations while ensuring transparency and alignment with recruiting objectives. • Plan and implement controlled experiments to test new recommendation mechanisms, validate supply projection accuracy, and optimize school engagement strategies across different markets and role families. • Partner with recruiting program managers, recruiters, and downstream engineering teams to translate ambiguous talent supply challenges into well-defined scientific formulations with measurable outcomes. About the team Our team focuses on understanding and improving the experience of both job seekers and the recruiters who support them. You'll be at the intersection of people, data, and technology—solving fascinating problems that directly impact how we hire the best talent globally.

Amazon's EU International Technology (EU INTech) organisation is creating new ways for customers to discover products through innovative customer experiences. Our team lead AI-native practices to make the path to product effortless, globally — experiment fast, grow our people, and deliver what customers feel. We are a science and engineering team within EU INTech, responsible for designing and developing AI/ML science solutions. We innovate on the frontlines of customer experience WW across different categories: Healthcare, Everyday Essentials, Groceries, Amazon Haul. We work across the full customer journey from search to post-purchase. We are located in the Madrid Technical Hub. We are looking for an Applied Scientist who is passionate about solving highly ambiguous and challenging problems at global scale. This is a hands-on, end-to-end applied science role where you will own the full lifecycle of science solutions — from business problem analysis and science plan design, through development and experimentation, to production deployment. We are looking for AI/ML experts with knowledge on ranking, computer vision, recommendation systems, search, and customer experience design. What makes this role unique: • End-to-end ownership – You will analyse business problems, map them to science plans, and design and develop solutions from ideation to production. We are owners of the full science lifecycle. • Applied science with a research edge – While our focus is on delivering applied science solutions that drive measurable business impact, our team actively pushes the state of the art in areas such as computer vision and Generative AI. Hands-on execution – We need scientists who thrive in building, experimenting, and shipping. What We're Looking For • A scientist who can independently analyse any business problem and design a rigorous science approach to solve it • Strong hands-on engineering skills — you build and ship, not just theorise • Deep expertise in one or more of: computer vision, generative AI, recommendation systems, ranking, or NLP • Experience taking ML models from research to production at scale • Comfort with ambiguity and the ability to structure complex, undefined problems • A passion for customer-centric innovation and measurable impact • A strong communicator capable to adapt the message from a science audience, to engineering or leadership Key job responsibilities - Analyse complex business problems and translate them into well-defined science plans with clear milestones and success criteria - Design, develop, and deliver ML/AI models end-to-end — from research and prototyping through to production systems at Amazon scale and extending solutions going beyond the state of the art - Work with state-of-the-art models in computer vision, ranking and generative AI to power new customer experiences globally - Own major science challenges for the team, driving solutions from ideation through experimentation to production deployment - Collaborate with a variety of roles and partner teams around the world to deliver integrated solutions - Influence scientific direction and best practices across the team. - Maintain high quality standards on team deliverables - Contribute to expanding the state of the art in computer vision, ranking and GenAI through publications and internal knowledge sharing

Amazon Search is building a first-of-its-kind AI-powered visual search experience that lets customers describe products they're imagining, instantly see AI-generated images in response, and tap those images to search for matching products to shop. We are transforming the search engine into a shopping engine by leveraging advances in generative AI and multimodal understanding. We are seeking an Applied Scientist II to join the Visual Search Science team and push the boundaries of generative AI and multimodal retrieval at Amazon scale. You will work at the intersection of diffusion models, large language models (LLMs), and multimodal search to build systems that generate product visualizations in real time and connect them to Amazon's billions-scale catalog. The ideal candidate has deep expertise in one or more of the following areas: text-to-image generation, multimodal retrieval, LLM-based classification, AI safety and content moderation, or retrieval-conditioned generation. You will operate with startup-level autonomy backed by the resources of Amazon Search, serving hundreds of millions of customers worldwide through GPU-distributed inference systems that generate and rank results in real time. Key job responsibilities You will design, train, and optimize generative AI models for real-time product image generation, ensuring outputs meet strict latency requirements while maintaining high visual quality and query alignment. You will develop multimodal retrieval systems that connect AI-generated images to Amazon's billions-scale product catalog, optimizing for recall and ranking relevance across product categories. A core part of the role involves building LLM-based classifiers for visual intent detection, query understanding, and safety filtering within real-time latency budgets. You will advance AI safety science through defense-in-depth approaches including embedding-space classifiers, adversarial data engines, and post-generation content moderation. You will design and execute large-scale online experiments to measure impact on customer engagement, search success, and business metrics, defining evaluation frameworks that combine automated metrics with human judgment. You will collaborate with engineering, product, and design teams to architect GPU-intensive inference pipelines serving real-time traffic at scale, and contribute to Amazon's scientific community through publications and patents. About the team The Visual Search Science team is pioneering generative AI for shopping within Amazon Search. We sit at the intersection of computer vision, natural language processing, and information retrieval building systems that help customers visualize what they're looking for and seamlessly discover matching products. Our team operates with speed and autonomy while leveraging Amazon's massive scale, GPU infrastructure, and product catalog. We are a tight-knit group of scientists and engineers who value rigorous experimentation, creative problem-solving, and shipping innovations that customers love. We collaborate closely with partner teams across Search organization.

Join Amazon's Global FP&A Technology (GFT) team as a Data Scientist, where you'll shape the future of FP&A operations by building the forecasting and AI capabilities behind Amazon's financial planning. As part of GFT's mission to streamline, optimize, and drive financial excellence through technology, you'll work closely with Corporate FP&A teams and cross-functional stakeholders to develop scalable data science solutions that support strategic finance objectives. Your work will contribute directly to enhancing reporting, planning, cost allocations, and business enablement tools that empower finance teams across the organization. The models you build here ship to production and directly influence how Amazon plans its finances. Our forecasts drive stock-based compensation — a P&L expense of over $20B a year — and the headcount outlook spanning Amazon's ~1.5M employees, feeding the OP1, OP2, and Board-level planning cycles. A growing part of our charter is building AI capabilities that take on repetitive work in finance. Today this work takes many manual hours per cycle, spans disconnected tools and relies on repeated handoffs. This is the forward-looking edge of GFT, and a space where you can build agents and AI systems that finance teams use directly. We are looking for a results-driven scientist to join our team in Seattle. You will work with FP&A teams, product managers, software engineers, data engineers, UX designers, and front-end engineers to understand key requirements, and you'll lead the design and development of data science products and services. The ideal candidate brings strong problem-solving skills, stakeholder communication skills, and the ability to balance technical rigor with delivery speed and customer impact. This is a great opportunity for someone looking to drive the next generation of data science architecture, design, and development that scales to support Amazon's business growth and the FP&A function. Key job responsibilities 1. Apply a range of data science methodologies — statistical modeling, machine learning, and time series analysis — to solve complex forecasting challenges. 2. Lead the end-to-end lifecycle of forecasting models — from research and experimentation through production launch — including defining success metrics, obtaining stakeholder sign-off, and managing rollout in collaboration with software and data engineering. 3. Run large-scale exploratory data analysis and rigorous experiments at scale to uncover patterns, evaluate models, and improve performance. 4. Partner with finance stakeholders, engineers, and other scientists to understand customer needs and deliver solutions that meet them. 5. Translate complex research findings into clear, factually correct documents and explain technical concepts to technical and non-technical audiences. About the team GFT team is a Finance Technology team within Corp FP&A. On our team, we enjoy a unique vantage point into everything happening within Amazon. As part of that, this role would be part of a team that is responsible for Company’s enterprise-wide financial planning & analytics environment. The data flowing through our platform directly contributes to decision-making by our CFO and all levels of finance leadership. If you’re passionate about building tools that enhance productivity, improve financial accuracy, reduce waste, and improve work-life harmony for a large and rapidly growing finance user base, come join us!

The AWS Marketplace Science team seeks a talented Applied Scientist. AWS Marketplace is one of the world's largest B2B software and service discovery platforms, generating rich multi-modal signals that create uniquely challenging problems at the intersection of large-scale information retrieval, generative AI, and agentic systems. You'll operate at the frontier of applied science where your models directly shape purchasing decisions for the world's largest cloud ecosystem. The ideal candidate excels in translating complex scientific research into practical, high-impact solutions, demonstrating both technical excellence and a deep understanding of customer needs. They should bring proven depth in numerous domains across information retrieval, recommendations, and agentic systems while remaining committed to mentoring others and fostering a culture of innovation and collaboration. The position offers a unique opportunity to influence how businesses worldwide discover and adopt software solutions. Key job responsibilities - Lead the research, design, and development of advanced AI/ML systems for information retrieval and agentic systems - Identify and evaluate emerging scientific techniques and technologies, translating research into practical, scalable solutions - Drive evaluation and hypothesis testing to continuously improve performance and relevance of search and recommendation systems - Collaborate with cross-functional teams, such as Product and Engineering leaders, to translate scientific innovations into customer value - Mentor Scientists and influence scientific approach across the organization About the team Mentorship and Career Growth We invest in your growth as a scientist. You'll collaborate closely with a community of applied scientists and research engineers tackling problems across search, recommendations, and generative AI. We support conference attendance and publication at top venues (NeurIPS, ICML, KDD, SIGIR), provide mentorship from senior scientists, and encourage the open exchange of ideas through internal science reading groups and seminars. Whether you want to deepen your technical expertise or grow into science leadership, we'll help you build a career defined by scientific impact. 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. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness.

Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more, all with the shared goal of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments, and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems. Recruiting Agents and Candidate Voice team is revolutionizing how Amazon finds and connects with talent worldwide! We're looking for an experienced Applied Scientist to design and implement agentic solutions that help millions of candidates find their dream jobs at Amazon. Key job responsibilities • Design and architect AI-powered agentic solutions that help candidates navigate Amazon's hiring process, including scoping requirements, identifying dependencies and constraints, and creating robust scientific and technical designs that balance candidate experience with system scalability. • Implement and deploy conversational AI agents leveraging state-of-the-art LLM and GenAI technologies to enable candidates to explore job opportunities, understand role requirements, and receive personalized guidance throughout their hiring journey. • Develop rigorous evaluation frameworks to measure agent effectiveness, candidate satisfaction, and hiring outcomes—continuously iterating on models to improve accuracy, fairness, and user experience across millions of candidate interactions. • Collaborate cross-functionally with Research Scientists, Software Engineers, and Product teams to integrate agentic solutions into Amazon's candidate-facing platforms, ensuring seamless deployment and alignment with broader Talent Acquisition goals. • Drive innovation in agentic AI research by staying current with advances in NLP, LLMs, and autonomous agent architectures, while contributing to the scientific community through publications, internal tech talks, and knowledge sharing. About the team Our team focuses on understanding and improving the experience of both job seekers and the recruiters who support them. You'll be at the intersection of people, data, and technology—solving fascinating problems that directly impact how we hire the best talent globally.

Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more, all with the shared goal of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments, and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems. Recruiting Agents and Candidate Voice team is revolutionizing how Amazon finds and connects with talent worldwide! We're looking for an experienced Applied Scientist to design and implement agentic solutions that help millions of candidates find their dream jobs at Amazon. Key job responsibilities • Design and architect AI-powered agentic solutions that help candidates navigate Amazon's hiring process, including scoping requirements, identifying dependencies and constraints, and creating robust scientific and technical designs that balance candidate experience with system scalability. • Implement and deploy conversational AI agents leveraging state-of-the-art LLM and GenAI technologies to enable candidates to explore job opportunities, understand role requirements, and receive personalized guidance throughout their hiring journey. • Develop rigorous evaluation frameworks to measure agent effectiveness, candidate satisfaction, and hiring outcomes—continuously iterating on models to improve accuracy, fairness, and user experience across millions of candidate interactions. • Collaborate cross-functionally with Research Scientists, Software Engineers, and Product teams to integrate agentic solutions into Amazon's candidate-facing platforms, ensuring seamless deployment and alignment with broader Talent Acquisition goals. • Drive innovation in agentic AI research by staying current with advances in NLP, LLMs, and autonomous agent architectures, while contributing to the scientific community through publications, internal tech talks, and knowledge sharing. About the team Our team focuses on understanding and improving the experience of both job seekers and the recruiters who support them. You'll be at the intersection of people, data, and technology—solving fascinating problems that directly impact how we hire the best talent globally.

Alexa+ is the world’s best Generative AI powered personal assistant / agent for consumers, and is becoming the conversational AI interface for Amazon services with the launch of Alexa for Shopping on Amazon.com and Amazon mobile app. At Alexa Ads, we are creating industry's first and most advanced Agentic Advertising products to drive Agentic Commerce. We are seeking an Applied Scientist to join our newly expanding team in India focused on Alexa Agentic/Conversational Ads and Personalization. In this role, you will build machine learning models that seamlessly and naturally integrate relevant advertising into the Alexa experience while deeply personalizing user interactions. You will work closely with other scientists, engineers, and product managers to take models from conception to production. Key job responsibilities - Design, develop, and evaluate innovative machine learning and deep learning models for natural language processing (NLP), recommendation systems, and personalization. - Conduct hands-on data analysis and build scalable ML pipelines. - Design and run A/B experiments to measure the impact of new models on customer experience and ad performance. - Collaborate with software development engineers to deploy models into high-scale, real-time production environments. About the team We are building a new science team in Bangalore to solve some of the most impactful problems in computational advertising. This isn't about tweaking existing models as we are rethinking how ads are ranked, priced, and personalized across voice-first and screen-first surfaces. These are problems that don't have textbook solutions. Key points to note about the team: 🧪 Greenfield team - you are not joining a mature org with rigid processes. You will shape the science roadmap, pick the problems, and define the culture from day one. 📈 Direct business impact — your models directly drive revenue. No yearly cycles to see if your work matters. 🌏 Global scope, local autonomy — collaborate with scientists and engineers across Seattle, Sunnyvale, and Bangalore, but own your problem space end-to-end. 🎓 Ship AND Publish: We encourage top-tier publications (NeurIPS, ACL, EMNLP, KDD, ICML, WWW) while ensuring your research hits production.

At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us. ABOUT THIS ROLE As an Applied Scientist, you will solve large complex real-world problems at scale, draw inspiration from the latest science and technology to empower undefined/untapped business use cases, delve into customer requirements, collaborate with tech and product teams on design, and create production-ready models that span various domains, including Machine Learning (ML), Artificial Intelligence (AI) and Generative AI, Natural Language Processing (NLP), Reinforcement Learning (RL), real-time and distributed systems. ABOUT YOU Your work will focus on inventing or adapting scientific approaches, models, and algorithms driven by customer needs at the project level. You will develop components and/or end-to-end solutions that are deployed into production or directly support production systems, delivering consistently high-quality work that meets both scientific and engineering best practices. You will develop reusable science components and services that resolve architecture deficiencies and customers’ pain points, while making technical trade-offs for long-term/short- term. You will work semi-autonomously to deliver solutions, contribute to research papers at peer-reviewed venues when appropriate, and document your work thoroughly to enable others to understand and reproduce it. Your decision-making will consistently incorporate robust, data-driven business and technical judgment. You will collaborate with other scientists to raise the bar of both scientific and engineering complexity for the team and to foster valuable scientific partnership opportunities to help/guide science decisions. We work in a highly collaborative, fast-paced environment where scientists, engineers, and product managers work to test and build scalable foundational capabilities, as well as customer facing experiences. You will have the opportunity to innovate and think big within your projects scope, implement optimization services and algorithms, and influence the experiences of millions of customers. We are looking for a results-oriented Applied Scientist with deep knowledge in ML, NLP, Deep Learning, GenAI, and/or large-scale distributed computation. As an Applied Scientist, you will... - Understand use cases across the business and adopt/extend/design/invent solutions/models that are scalable, efficient, and automated for difficult problems that are not well defined - Work closely with fellow scientists and software engineers (at Audible and Amazon) to build and productionize models, deliver novel and highly impactful features - Review models of peers for the purpose of reducing and managing risk to the business, while improving customer experience - Design, develop, and deploy modeling techniques and solutions for Content Understanding, Recommendations, GenAI-based product features, by employing a wide range of methodologies, working from simple to complex - Contribute to initiatives that employ the most recent advances in ML/AI in a fast-paced, experimental environment - Push the boundary of innovation ABOUT AUDIBLE Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.

This position is based in Bangalore, India The Last Mile team helps get packages from delivery stations to a customer’s doorstep. To provide new innovations for customers, awe are inventing the next-generation smart delivery operation. We are combining innovative mobile and IoT technologies, data streams (video, vehicle telematics, location, and presence), together with machine learning models and algorithms – all to create solutions that allow us to deliver faster, and with more confidence. Playing a key role in the Last Mile Driver Experience team, as a Applied Scientist you will be responsible for building machine learning models and algorithms in areas including mapping and location, pattern detection in sensor data, and computer vision. Using your research, you will work with your engineering and product management peers to drive designs from ideation through development and into production. You will bring your experience of research for similar products and solutions, preferably in consumer or industrial verticals. This role requires autonomy and an ability to deliver results, often within the ambiguity of building a v1 product. You will need to work efficiently to build the right things with limited guidance, raising the bar to create an amazing experience for our customers.