Careers

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to build industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As an Applied Scientist with the AGI team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in conversational AI. About the team Our team’s mission is to deliver general-purpose multimodal foundation models enabling seamless speech-to-speech functions across a wide range of applications. We own pre-training (PT) and supervised fine-tuning (SFT) of LLMs. We partner with other teams to achieve state-of-the-art performance in all aspects of speech functions. We support product teams to deliver innovative conversational AI solutions to a broad set of customers and use cases.

Advertising at Amazon is a fast-growing multi-billion dollar business that spans across desktop, mobile and connected devices; encompasses ads on Amazon and a vast network of hundreds of thousands of third party publishers; and extends across US, EU and an increasing number of international geographies. One of the key focus areas is Traffic Quality where we endeavour to identify non-human and invalid traffic within programmatic ad sources, and weed them out to ensure a high quality advertising marketplace. We do this by building machine learning and optimization algorithms that operate at scale, and leverage nuanced features about user, context, and creative engagement to determine the validity of traffic. The challenge is to stay one step ahead by investing in deep analytics and developing new algorithms that address emergent attack vectors in a structured and scalable fashion. We are committed to building a long-term traffic quality solution that encompasses all Amazon advertising channels and provides state-of-the-art traffic filtering that preserves advertiser trust and saves them hundreds of millions of dollars of wasted spend. We are looking for talented Research scientists who enjoy working on creative machine learning algorithms and thrive in a fast-paced, fun environment. A Research Scientist is responsible for solving inherently hard problems in advertising fraud detection using deep learning, self-supervised techniques, representation learning and advanced clustering. An ideal candidate should have strong depth and breadth knowledge in machine learning, data mining and statistics. Traffic quality systems process billions of ad-impressions and clicks per day, by leveraging cutting-edge open source technologies like Spark, Redis and Amazon's cloud services like EC2, S3, EMR, DynamoDB and RedShift. The candidate should have reasonable programming and design skills to manipulate unstructured and big data and build prototypes that work on massive datasets. The candidate should be able to apply business knowledge to perform broad data analysis as a precursor to modeling and to provide valuable business intelligence.

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to help build industry-leading technology with multimodal systems. Key job responsibilities As an Applied Scientist with the AGI team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with multimodal systems. Your work will directly impact our customers in the form of products and services that make use of vision and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with multimodal Large Language Models (LLMs) and Generative Artificial Intelligence (GenAI) in Computer Vision. About the team The AGI team has a mission to push the envelope with multimodal LLMs and Gen AI in Computer Vision, in order to provide the best-possible experience for our customers.

Join the AWS Perimeter Protection team as a Data Scientist, where you will play a crucial role in developing cutting-edge AI/ML-based security solutions. You will collaborate closely with our security engineers and researchers to build innovative offerings that complement our existing security services, including Web Application Firewall, DDoS Protection, Bot Management, Network Firewall, and Infrastructure protection. With services offered across all AWS regions and handling trillions of requests per week, you will operate at a massive scale, ensuring robust and efficient security measures. Key job responsibilities - Develop and implement advanced AI/ML models and algorithms to enhance the capabilities of our security services, enabling proactive threat detection, mitigation, and protection against evolving cyber threats. - Collaborate with security engineers and researchers, to understand business/domain requirements, analyze data patterns, and translate insights into actionable solutions. - Design and drive implementation of data pipelines and ETL processes to ingest, process, and analyze large-scale security data from multiple sources, ensuring data quality and integrity. - Conduct in-depth data analysis, feature engineering, and model evaluation to continuously improve the performance and accuracy of AI/ML-based security solutions. - Participate in the development and deployment of AI/ML models into production environments, ensuring scalability, reliability, and performance at cloud scale. - Collaborate with cross-functional teams to ensure seamless integration of AI/ML solutions with our security services and infrastructure. - Contribute to the development of best practices, documentation, and knowledge-sharing within the team and the broader organization. - Engage in research and exploration of emerging technologies and techniques relevant to AI/ML-based security solutions, stay up-to-date with the latest trends cybersecurity, and incorporate new techniques and methodologies into our security offerings. About the team About AWS 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 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 (gender diversity) conferences, inspire us to never stop embracing our uniqueness. 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. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our US Amazon offices. This team is part of AWS Infrastructure Services: AWS Infrastructure Services (AIS) AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

Join the AWS Perimeter Protection team as an Applied Data Scientist, where you will play a crucial role in developing cutting-edge AI/ML-based security solutions. You will collaborate closely with our security engineers and researchers to build innovative offerings that complement our existing security services, including Web Application Firewall, DDoS Protection, Bot Management, Network Firewall, and Infrastructure protection. With services offered across all AWS regions and handling trillions of requests per week, you will operate at a massive scale, ensuring robust and efficient security measures. Key job responsibilities - Develop and implement advanced AI/ML models and algorithms to enhance the capabilities of our security services, enabling proactive threat detection, mitigation, and protection against evolving cyber threats. - Collaborate with security engineers and researchers, to understand business/domain requirements, analyze data patterns, and translate insights into actionable solutions. - Design and drive implementation of data pipelines and ETL processes to ingest, process, and analyze large-scale security data from multiple sources, ensuring data quality and integrity. - Conduct in-depth data analysis, feature engineering, and model evaluation to continuously improve the performance and accuracy of AI/ML-based security solutions. - Participate in the development and deployment of AI/ML models into production environments, ensuring scalability, reliability, and performance at cloud scale. - Collaborate with cross-functional teams to ensure seamless integration of AI/ML solutions with our security services and infrastructure. - Contribute to the development of best practices, documentation, and knowledge-sharing within the team and the broader organization. - Engage in research and exploration of emerging technologies and techniques relevant to AI/ML-based security solutions, stay up-to-date with the latest trends cybersecurity, and incorporate new techniques and methodologies into our security offerings. About the team About AWS 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 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 (gender diversity) conferences, inspire us to never stop embracing our uniqueness. 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. This team is part of AWS Infrastructure Services: AWS Infrastructure Services (AIS) AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

Are you passionate about transforming the digital reading and publishing landscape? Team is at the forefront of revolutionizing the publishing and reading experience for millions worldwide. We are seeking innovative Applied Scientists to join us at the forefront of the digital transformation in the publishing industry. Our team is dedicated to enhancing the book publishing and reading experience using cutting-edge AI technology. We strive to streamline the publishing lifecycle, improve digital reading, and empower book publishers through innovative AI tools and solutions to grow their business on Amazon. We are building a holistic team focused on leveraging advances in AI to improve the Reading experience for Kindle customers, and the Publishing experience for book content creators and distributors; and this role is specifically for an Applied Scientist who will focus on making publishers lives easier through AI. We are building a Publishing & Reading Science team and looking for Scientists, who are passionate about Reading and are willing to take Reading to the next level. Every Book is a complex structure with different entities, layout, format and semantics, with more than 17MM eBooks in our catalog across different publishers. We are looking for experts in all domains like core NLP, Generative AI, CV and Deep Learning Techniques for unlocking capabilities like analysis, enhancement, curation, moderation, translation, transformation and generation in Books based on Content structure, features, Intent, Synthesis and publisher details. Scientists will focus on Inside the book content and semantically learn the different entities to enhance the Reading and publishing experience overall (Kindle & beyond). They have an opportunity to influence in 3 major phases of life-cycle - Publishing (Creation of Books process), Reading experience (building engaging features & representation in the book thereby driving reading engagement) and Reporting (improvement through their sales & business growth). Key job responsibilities - Inspect AI initiatives across Amazon to identify how these can be applied and scaled to book publishers or publishing workflows. - Participate in team design, scoping and prioritization discussions. You must be able to map a business goal to a scientific problem, and map business metrics to technical metrics. - Spearhead the design and implementation of new features and algorithms based on thorough research and collaboration with cross-functional teams. - You have expertise in one of the applied science disciplines, such as machine learning, natural language processing, computer vision, Deep learning - You are able to use reasonable assumptions, data, and customer requirements to solve problems. - You initiate the design, development, execution, and implementation of smaller components with input and guidance from team members. - You work with SDEs to deliver solutions into production to benefit customers or an area of the business. - You assume responsibility for the code in your components. You write secure, stable, testable, maintainable code with minimal defects. - You understand basic data structures, algorithms, model evaluation techniques, performance, and optimality tradeoffs. - You follow engineering and scientific method best practices. You get your designs, models, and code reviewed. You test your code and models thoroughly - You participate in team design, scoping and prioritization discussions. You are able to map a business goal to a scientific problem and map business metrics to technical metrics. - You invent, refine and develop your solutions to ensure they are meeting customer needs and team goals. You keep current with research trends in your area of expertise and scrutinize your results. - Experience in mentoring junior scientists A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test solutions to improve our experience. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, model development and productionizing the same. You will mentor other scientists, review and guide their work, help develop roadmaps for the team.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! As an Applied Science Manager in Machine Learning, you will: - Directly manage and lead a cross-functional team of Applied Scientists, Data Scientists, Economists, and Business Intelligence Engineers. - Develop and manage a research agenda that balances short term deliverables with measurable business impact as well as long term investments. - Lead marketplace design and development based on economic theory and data analysis. - Provide technical and scientific guidance to team members. - Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment - Advance the team's engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner. - Develop science and engineering roadmaps, run annual planning, and foster cross-team collaboration to execute complex projects. - Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management. - Collaborate with business and software teams across Amazon Ads. - Stay up to date with recent scientific publications relevant to the team. - Hire and develop top talent, provide technical and career development guidance to scientists and engineers within and across the organization. Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video ~ https://youtu.be/zD_6Lzw8raE

The Private Brands Discovery team designs innovative machine learning solutions to drive customer awareness for Amazon’s own brands and help customers discover products they love. Private Brands Discovery is an interdisciplinary team of Scientists and Engineers, who incubate and build disruptive solutions using cutting-edge technology to solve some of the toughest science problems at Amazon. To this end, the team employs methods from Natural Language Processing, Deep learning, multi-armed bandits and reinforcement learning, Bayesian Optimization, causal and statistical inference, and econometrics to drive discovery across the customer journey. Our solutions are crucial for the success of Amazon’s own brands and serve as a beacon for discovery solutions across Amazon. This is a high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and engineers. As a scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics and business teams. Key job responsibilities - Drive applied science projects in machine learning end-to-end: from ideation over prototyping to launch. For example, starting from deep scientific thinking about new ways to support customers’ journeys through discovery, you analyze how customers discover, review and purchase Private Brands to innovate marketing and merchandising strategies. - Propose viable ideas to advance models and algorithms, with supporting argument, experiment, and eventually preliminary results. - Invent ways to overcome technical limitations and enable new forms of analyses to drive key technical and business decisions. - Present results, reports, and data insights to both technical and business leadership. - Constructively critique peer research and mentor junior scientists and engineers. - Innovate and contribute to Amazon’s science community and external research communities.

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the extreme. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.

Amazon's Global Talent Management and Compensation (GTMC) Center for Applied Science and Economics (CASE) builds science models supporting employee career-related experiences such as their evaluation, learning and development, onboarding, and promotion for Amazonians. Additionally, the team conducts experiments for a wide range of employee and talent-related product features, and measures the impact of product and program initiatives in enhancing our employees' career experiences at Amazon. Amazon's GTMC team is looking for Economists who are highly specialized in the field of macroeconomics and time series forecasting. The economist will enhance science models by enabling them to adapt to external talent dynamics, enabling personalized, consistent, and high-impact employee experiences across the talent lifecycle. This will make the models more responsive to evolving market conditions and enhance the alignment of Amazon-wide talent strategies with team and organization-specific strategic objectives. Key job responsibilities The Economists within GTMC will be primarily involved in building advanced forecasting and time series models that account for the nuances of aggregate econometric modeling within the HR space. This includes modeling the inter-relationship of various talent outcomes, as well as scenario planning and modeling tasks to quantify the implications of external macro as well as industry-level shocks on key HR talent outcomes. The economists will closely collaborate with a range of scientists from different backgrounds, as well as program and product leaders, to implement and assess the science solutions into the company's products.