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Amazon Leo is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband connectivity to unserved and underserved communities around the world. As a Systems Engineer, this role is primarily responsible for the design, development and integration of communication payload and customer terminal systems. The Role: Be part of the team defining the overall communication system and architecture of Amazon Leo’s broadband wireless network. This is a unique opportunity to innovate and define groundbreaking wireless technology at global scale. The team develops and designs the communication system for Leo and analyzes its overall system level performance such as for overall throughput, latency, system availability, packet loss etc. This role in particular will be responsible for leading the effort in designing and developing advanced technology and solutions for communication system. This role will also be responsible developing advanced physical layer + protocol stacks systems as proof of concept and reference implementation to improve the performance and reliability of the LEO network. In particular this role will be responsible for using concepts from digital signal processing, information theory, wireless communications to develop novel solutions for achieving ultra-high performance LEO network. This role will also be part of a team and develop simulation tools with particular emphasis on modeling the physical layer aspects such as advanced receiver modeling and abstraction, interference cancellation techniques, FEC abstraction models etc. This role will also play a critical role in the integration and verification of various HW and SW sub-systems as a part of system integration and link bring-up and verification. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

Amazon Strategic Account Services (SAS) Tech Organization is looking for an Applied Scientist Applied Scientist who can autonomously drive scientific innovations from research to production, developing sophisticated AI solutions that serve both Amazon's global seller base and internal Marketplace Consultants. Working in a highly collaborative environment, you'll leverage expertise in machine learning, operations research, and statistics to translate theoretical advances in LLMs, probabilistic modeling, and optimization into practical applications. The role demands strong capabilities in prototyping and iterative improvement, bridging cutting models with real-world applications while maintaining scientific rigor and measurable business impact. Key job responsibilities - Lead the development of sophisticated AI solutions leveraging deep learning, LLMs, and advanced machine learning techniques to transform both seller operations and internal consultancy capabilities at scale - Define and drive long-term scientific vision for the organization, translating complex business challenges into innovative technical solutions that advance the state-of-the-art in applied machine learning - Design and implement advanced ML architectures combining multiple learning paradigms - from reinforcement learning and causal inference to predictive modeling - to tackle critical marketplace challenges - Architect next-generation recommendation and optimization systems that handle complex multi-dimensional constraints while maintaining robustness and interpretability at scale - Drive end-to-end development of AI applications from research through production, collaborating with engineering teams to ensure successful deployment and conducting rigorous A/B experiments to validate impact - Pioneer novel applications of foundation models and generative AI, developing sophisticated evaluation frameworks while maintaining Amazon's high standards for accuracy and reliability - Lead technical discussions across organizational boundaries, effectively communicating complex scientific concepts to diverse stakeholders while staying at the forefront of ML/AI research advancements About the team What is Amazon Strategic Account Services (SAS)? The SAS team aims to accelerate the full potential of our Sellers, helping them to navigate the increasing complexity of the e-commerce space. Our team provides in-depth strategic consultancy using a data-driven, collaborative, and a Customer-focused approach to achieve commercial goals of Amazon Sellers.

The Principal Applied Scientist will own the science mission for building next-generation proactive and autonomous agentic experiences across Alexa AI's Personalization, Autonomy and Proactive Intelligence organization. You will technically lead a team of applied scientists to harness state-of-the-art technologies in machine learning, natural language processing, LLM training and application, and agentic AI systems to advance the scientific frontiers of autonomous intelligence and proactive user assistance. The right candidate will be an inventor at heart, provide deep scientific leadership, establish compelling technical direction and vision, and drive ambitious research initiatives that push the boundaries of what's possible with AI agents. You will need to be adept at identifying promising research directions in agentic AI, developing novel autonomous agent solutions, and translating advanced AI research into production-ready agentic systems. You will need to be adept at influencing and collaborating with partner teams, launching AI-powered autonomous agents into production, and building team mechanisms that will foster innovation and execution in the rapidly evolving field of agentic AI. This role represents a unique opportunity to tackle fundamental challenges in how Alexa proactively understands user needs, autonomously takes actions on behalf of users, and delivers intelligent assistance through state-of-the-art agentic AI technologies. As a science leader in Alexa AI, you will shape the technical strategy for making Alexa a truly proactive and autonomous agent that anticipates user needs, takes intelligent actions, and provides seamless assistance without explicit prompting. Your team will be at the forefront of solving complex problems in agentic reasoning, multi-step task planning, autonomous decision-making, proactive intelligence, and context-aware action execution that will fundamentally transform how users interact with Alexa as an intelligent agent. The successful candidate will bring deep technical expertise in machine learning, natural language processing, and agentic AI systems, along with the leadership ability to guide talented scientists in pursuing ambitious research that advances the state of the art in autonomous agents, proactive intelligence, and AI-driven personalization. Experience with multi-agent systems, reinforcement learning, goal-oriented dialogue systems, and production-scale agentic architectures is highly valued. You will lead the development of breakthrough capabilities that enable Alexa to: 1) proactively anticipate user needs through advanced predictive modeling and contextual understanding; 2) autonomously execute complex multi-step tasks with minimal user intervention; 3) reason and plan intelligently across diverse user goals and environmental contexts; 4) learn and adapt continuously from user interactions to improve agentic behaviors; 5) coordinate actions seamlessly across multiple domains and services as a unified intelligent agent. This is a unique opportunity to define the future of conversational AI agents and build technology that will impact hundreds of millions of customers worldwide. Key job responsibilities Technical Leadership - Lead complex research and development projects - Partner closely with the T&C Product and Engineering leaders on the technical strategy and roadmap - Evaluate emerging technologies and methodologies - Make high-level architectural decisions Technical leadership and mentoring: - Mentor and develop technical talent - Set team project goals and metrics - Help with resource allocation and project prioritization from technical side Research & Development - Drive innovation in applied science areas - Translate research into practical business solutions - Author technical papers and patents - Collaborate with academic and industry partners About the team PAPI (Personalization Autonomy and Proactive Intelligence) aims to accelerate personalized and intuitive experiences across Amazon's customer touchpoints through automated, scalable, self-serve AI systems. We leverage customer, device, and ambient signals to deliver conversational, visual, and proactive experiences that delight customers, increase engagement, reduce defects, and enable natural interactions across Amazon touch points including Alexa, FireTV, and Mobile etc. Our systems offer personalized suggestions, comprehend customer inputs, learn from interactions, and propose appropriate actions to serve millions of customers globally.

Do you ever struggle to explain your work? How's this: "Do you shop at Amazon? Do you know that box that says 'Add to Cart' and shows a price? Our team owns the model which picks that offer and the customer experience around the display of the offer price and the elements surrounding the 'Add to Cart' button which inform a purchase decision. We pick and display offers several billion times a day across all surfaces (mobile app, mobile web, desktop, Alexa shopping) worldwide. Our mission is to be the world’s first and most trusted choice for every customer on earth to discover and evaluate any product or service. Our team blends machine learning models to rank and select the best offer from the most trusted merchant for all products sold on Amazon along with a world-class front-end user experience for offer comparison to our global customers. We are responsible for the experiences and services that enable developers, including our own, to create tailored shopping experiences for every customer, product, business and marketplace offered by Amazon. We build scalable and extensible frameworks which allow for many teams at Amazon to innovate within the Offers Experience in a federated manner. If you are passionate about influencing and delivering the next-generation Amazon customer buying experience, we want to meet you. We are looking for a Senior Applied Scientist to join one of the most impactful and visible teams in Amazon. In this role you will work with business stakeholders throughout Amazon and provide technical direction and business expertise to strategize and help launch new businesses and features for our customers. You will use data to justify customer friendly decisions and present customer and financial impact of the changes we make to our stakeholders. You will work closely with other scientists, engineers, product managers, TPMs, managers, and senior leadership team to understand and drive business impact. Successful candidates will have experience working on multiple projects with different stakeholders, make data driven decisions, have strong communication skills to interact with executives, non-technical and technical individuals and have a high technical bar along with a passion for people and project management. This is an opportunity to work with a team that drives one of the most coveted real estate in the E-commerce, the Amazon ‘Buy Box’ on Amazon Product Detail Page, Amazon Search Page , multiple buying widgets etc. on the Amazon desktop, mobile and tablet environments. Key job responsibilities * Build, innovate and maintain FMA's key offer selection algorithms * Collaborate with peer scientists and partner organizations to align on strategic algorithmic inputs * Research and deliver innovative techniques for ranking, simulation and evaluation systems * Build and maintain AI, ML and LLM integrations

As an Applied Scientist, you will be responsible for bringing new product designs through to manufacturing. You will work closely with multi-disciplinary groups including Product Design, Industrial Design, Hardware Engineering, and Operations, to drive key aspects of engineering of consumer electronics products. In this role, you will use expertise in physical sciences, theoretical, numerical or empirical techniques to create scalable models representing response of physical systems or devices, including: * Applying domain scientific expertise towards developing innovative analysis and tests to study viability of new materials, designs or processes * Working closely with engineering teams to drive validation, optimization and implementation of hardware design or software algorithmic solutions to improve product and customer risks * Establishing scalable, efficient, automated processes to handle large scale design and data analysis * Conducting research into use conditions, materials and analysis techniques * Tracking general business activity including device health in field and providing clear, compelling reports to management on a regular basis * Developing, implementing guidelines to continually optimize design processes * Using simulation tools like LS-DYNA, and Abaqus for analysis and optimization of product design * Using of programming languages like Python and Matlab for analytical/statistical analyses and automation * Demonstrating strong understanding across multiple physical science domains, e.g. structural, thermal, fluid dynamics, and materials * Developing, analyzing and testing structural solutions from concept design, feature development, product architecture, through system validation * Supporting product development and optimization through application of analysis and testing of complex electronic assemblies using advanced simulation and experimentation tools and techniques

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.

Join us at the forefront of Amazon's sustainability initiatives to work on environmental and social advancements that support Amazon's long-term worldwide sustainability strategy. At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people who are passionate about making a meaningful impact on communities and the environment while helping shape the future of sustainable business practices. The Worldwide Sustainability (WWS) organization capitalizes on Amazon's scale and speed to build a more resilient and sustainable company. We manage our social and environmental impacts globally and drive solutions that enable our customers, businesses, and the world to become more sustainable. Through innovative programs and strategic partnerships, we're creating lasting positive change in the communities where we operate while advancing Amazon's commitment to environmental stewardship and social responsibility. We are looking for a robotics scientist to build and operate the first autonomous materials discovery laboratory at Amazon. This role combines deep robotics expertise (motion planning, control, platform integration) with modern Physical AI approaches (vision-language-action models, sim-to-real transfer, agentic orchestration). You will design autonomous experimental workflows that integrate dexterous robotic platforms, analytical instruments, and AI-driven hypothesis generation into a closed-loop discovery pipeline — where foundation models drive hypothesis generation and experimental planning, validated on real hardware under real chemistry. This is not a pure research role. You will work directly with physical robots, laboratory instruments, and deployment pipelines. The work is expected to be published, but the primary measure of success is a working autonomous platform that generates scientific results. Materials science expertise is not required — the team includes domain scientists. What matters is strong AI and robotics foundations, scientific curiosity, and the drive to ship. Key job responsibilities - Develop, train, and benchmark robotic manipulation policies for materials synthesis and characterization using modern policy architectures (VLA architectures, diffusion policies). - Design and execute sim-to-real transfer strategies including domain randomization, physics parameter tuning, and visual domain adaptation for laboratory robotic systems. - Integrate robotic platforms and laboratory instruments into automated workflows via APIs (SiLA 2, or equivalent), building real-time data pipelines for multimodal experimental outputs. - Architect policy training pipelines combining teleoperation data, synthetic demonstrations, reinforcement learning, and imitation learning for dexterous lab manipulation. - Build production-grade agentic runtime systems — failure detection, retry logic, exception handling, and human-handoff protocols — for unattended experimental sessions. - Design and execute autonomous experimental campaigns applying active learning, Bayesian optimization, or RL to drive iterative materials discovery. - Drive technical design reviews and set scientific direction for the autonomous lab platform. A day in the life You build the Physical AI systems that power robotics in autonomous science lab, one where foundation models generate hypotheses, robots execute experiments, and closed-loop optimization discovers materials that did not exist yesterday. You train manipulation policies in simulation, transfer them to a physical cobot, and watch real chemistry validate (or invalidate) an AI-generated theory. The signal here is not a metric on a dashboard; it is a synthesizing and testing novel material with measurable sustainability impact. If you want your research to have physical weight, this is the lab. About the team Sustainability Science and Innovation (SSI) is a multi-disciplinary research team within WW Sustainability combining science, ML, economics, and engineering. The autonomous laboratory is a new capability being built from the ground up. You will work alongside computational materials scientists, chemists, and ML engineers — with access to AWS-scale compute and Amazon's supply chain for hardware. The work targets sustainability outcomes across packaging, building materials, and alternative fuels.

You will build and lead the economics research agenda for measurement, experimentation, and value attribution for Amazon's Devices & Services organization. Your team is the "truth layer" of the Intelligence Core — the shared economics and causal inference capability that serves all Devices product lines, marketing pods, and Finance leadership with causal evidence of what Devices are worth and whether our investments are working. This is not a traditional analytics or measurement role. You will own an active research program in experimentation design — identifying and executing the causal studies that produce the causal inputs for pricing decisions, marketing optimization, and portfolio strategy. Your outputs provide the causal evidence base that L8 peers and senior leadership consume to make billions of dollars in investment decisions across the D&S portfolio. You will also own the economic models that validate and drive execution across the full surface area of marketing spend for devices and services. Key job responsibilities Economic Value: • Downstream value attribution for all Devices product lines — Impact on Prime, subscription lift, consumer spending, advertising value • Alexa+ value isolation and cross-PL attribution • Causal frameworks connecting device sales to Prime acquisition, subscription retention, and ecosystem engagement Marketing Science & Measurement: • Build the marketing science function from scratch • Incrementality measurement for marketing spend across all channels • Attribution methodology, measurement standards, and cross-pod governance • Marketing ROI frameworks for use by category marketers • CCM certification methodology and scenario planning models for optimal investment allocation Experimentation: • Owning the estimation methodology, identification strategies, data inputs/outputs, and refresh cadence • You will build this team's analytics function with AI at its core from day one • Experimentation governance — managing interference across teams, setting standards for causal validity • Evaluation framework for AI agents and autonomous optimization systems

Are you passionate about solving big problems from ground-up? Do you enjoy building new state-of-the-art products at internet scale? Come lead the innovation in this startup team, vertical ad products. This is a green field problem without a known answer or a pattern to follow. We have ambitious vision to simplify full funnel advertising solutions, at scale, with specialized agentic AI-powered models and diversify the demand to strategic verticals including finserv, autos, locals.. etc. We are seeking an experienced Sr Data Scientist to drive innovation in our Ads Foundational Model. In this individual contributor role, you will apply advanced machine learning techniques to improve advertiser performance and customer experience. Key job responsibilities As a Data Scientist on this team, you will: 1. Develop and drive the science strategy for Ads Foundational Model (Ads-FM), aligning it with the program's objectives and overall business goals. 2. Identify high-impact opportunities within Ads-FM program and lead the ideation, planning, and execution of science initiatives to address them. 3. Build and deploy machine learning models using computer vision, natural language processing, and deep learning to evaluate and enhance ad effectiveness. 4. Develop algorithms that extract meaningful signals from image, video, and audio content to predict and improve customer engagement 5. Leverage Amazon's extensive data repository to create predictive models that generate actionable recommendations for more compelling ad creative 6. Collaborate with business leaders and cross-functional teams to implement ML-powered solutions 7. Contribute to the ML roadmap for the Ads-FM program through innovation and research.

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.