Machine Learning Science

The Amazon SageMaker Low-Code/No-Code team team is looking for a passionate, highly skilled and inventive Senior Applied Scientist with strong machine learning background to lead the development and implementation of state-of-the-art automated ML systems that aid the jobs of a data scientist and machine learning engineer with automation.As a Applied Scientist, you will play a critical role in driving the understanding of the development of automation techniques for machine learning and data science. You will handle Amazon-scale use cases with significant impact on our customers' experiences. Our team thrives on white-box understanding of machine learning and a connection to scientific principles (in addition to mathematical and statistical principles). Key job responsibilities- Create objective functions for automation of machine learning and data science.- Innovate new methods for evaluation, simplification, and creation of models for classification, regression, forecast and language modeling.- Research in advanced customer understanding and behavior modeling techniques.- Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in personal knowledge aggregation, processing, modeling, and verification- Design and execute experiments to evaluate the performance of state-of-the-art algorithms and models, and iterate quickly to improve results- Think Big about the arc of development of conversational assistant system personalization over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems- Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports- Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the teamA day in the life- Create prototypes- Educate engineers on design and implementation issues of automated machine learning systems- Help engineers with customer requestsAbout the teamThe LCNC team uses statistical, information-theoretic, and physical methods to automate the creation, tuning, and evaluation of models and to create data insights. We work across multiple AWS products, including AWS Sagemaker, to enhance the user experience by bringing more personal context and relevance to customer interactions.About AWSDiverse ExperiencesAWS 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 CultureHere 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 GrowthWe’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 BalanceWe 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 WorkWe 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 Utility Computing: Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language ...

The Amazon AGI SF Lab is focused on developing new foundational capabilities for enabling useful AI agents that can take actions in the digital and physical worlds. In other words, we’re enabling practical AI that can actually do things for us and make our customers more productive, empowered, and fulfilled. The lab is designed to empower AI researchers and engineers to make major breakthroughs with speed and focus toward this goal. Our philosophy combines the agility of a startup with the resources of Amazon. By keeping the team lean, we’re able to maximize the amount of compute per person. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research.If you’re interested in our particular philosophy of AI progress, reach out via AGI-SFLab-Jobs@amazon.com.Key job responsibilities- Develop cutting edge multimodal Large Language Models (LLMs) to observe, model and derive insights from manual workflows for automation- Work in a joint scrum with engineers for rapid invention, develop cutting edge automation agent systems, and take them to launch for millions of customers- Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in GenAI- Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results- Think big about the arc of development of GenAI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports- Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the teamBASIC QUALIFICATIONSPhD, or Master's degree and 5+ years of applied research experience3+ years of building machine learning models for business application experienceExperience programming in Java, C++, Python or related languageExperience with neural deep learning methods and machine learning ...

Amazon has the world’s most complex supply chain: we fulfill global demand for hundreds of millions of products at lightning fast delivery speeds. A core part of the operations is forecasting: We forecast the demand of hundreds of millions of products up to a year into the future. The forecasts are used to automatically order hundreds of millions worth of inventory weekly, decide where to place that inventory, and to establish labor plans for hundreds of warehouses.The Applied Scientist II will work with the Supply Chain Optimization Technologies (SCOT) Forecasting team and both business and engineering stakeholders worldwide to develop state of art machine learning models to forecast inbound shipment. The scientist develops novel algorithmic architectures, toward the ultimate goal of accurately predicting when and how Amazon receives shipments of millions of products world-wide. This drives down costs and enables the offer of lower prices and better in-stock selection for our customers.Working collaboratively, you will develop solutions to complex problems, such as designing the next generation of algorithms. As an Applied Scientist, you will continue to contribute to the research community, by working with other scientists across Amazon, as well as collaborating with academic researchers and publishing papers. Within SCOT Forecasting, our Science community values teamwork and recognizes the need to take chances and try new ideas that may fail. Furthermore, our builder culture means that Scientists and Software Development Engineers work closely together to invent and construct at a massive scale. Your work can be part of Amazon production system and result in concrete business impact. Key job responsibilities- Design, implement, and evaluate innovative models, agents, and software prototypes.- Collaborate with a team of experienced scientists to drive technological advancements.- Develop novel solutions to complex business problems in collaboration with partner teams.- Constructively critique peer research and mentor junior scientists and engineers- Contribute to Amazon's global science community through collaboration and publication of groundbreaking research.About the teamSupply Chain Optimization Technologies (SCOT) owns Amazon’s global inventory planning systems. We decide what, when, where, and how much we should buy to meet Amazon’s business goals and to make our customers happy. We decide how to place and move inventory within Amazon’s fulfillment network. We do this for hundreds of millions of items and hundreds of product lines worth billions of dollars of world-wide. Venturing beyond traditional operations research methods for sequential decision-making in inventory planning. The team combines empirical research and real world testing, backed by a robust theoretical foundation. BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Do you want to join an innovative team of scientists who leverage cutting-edge techniques like reinforcement learning (RL), large language models (LLMs), graph analytics, and machine learning to help Amazon provide the best customer experience by protecting Amazon customers from hackers and bad actors? Do you want to build advanced algorithmic systems that integrate these state-of-the-art techniques to help manage the trust and safety of millions of customers every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating sophisticated algorithms that combine RL, LLMs, graph embeddings, and traditional machine learning methods to solve complex real-world problems? Do you like to innovate, simplify, and push the boundaries of what's possible? If yes, then you may be a great fit to join the Amazon Account Integrity team, where you'll have the opportunity to work at the forefront of AI and machine learning, tackling challenging problems that have a direct impact on the security and trust of Amazon's customers.The Amazon Account Integrity team works to ensure that customers are protected from bad actors trying to access their accounts. Our greatest challenge is protecting customer trust without unjustly harming good customers. To strike the right balance, we invest in mechanisms which allow us to accurately identify and mitigate risk, and to quickly correct and learn from our mistakes. This strategy includes continuously evolving enforcement policies, iterating our Machine Learning risk models, and exercising high‐judgement decision‐making where we cannot apply automation.Please visit https://www.amazon.science for more informationBASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

The Devices and Services Security team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to secure the development of industry-leading Generative AI systems.As a Senior Applied Scientist with the Devices & Services Security team, you will lead the development of novel algorithms and modeling techniques to advance the state of the art with Generative AI 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 of security solutions with multimodal Large Language Models (LLMs) and Generative Artificial Intelligence (Gen AI).The Devices and Services (D&S) Security team works to ensure that Amazon devices and services are designed and implemented to the high standards required to maintain and enhance customer trust. The team develops security technologies for builder teams, performs penetration testing, and handles and tracks incident responses to resolution. The team is responsible for defining and executing on the security and privacy requirements for the entire organization.A day in the lifeDiverse ExperiencesAmazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Why Amazon Security?At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores.Inclusive Team CultureIn Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices.Training & Career GrowthWe’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life BalanceWe 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.BASIC QUALIFICATIONS- PhD, or Master's degree and 6+ years of applied research experience- 3+ years of building machine learning models for business application experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You'll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!Key job responsibilitiesWe seek strong Applied Scientists with domain expertise in machine learning and deep learning, transformers, generative models, large language models, computer vision and multimodal models. You will devise innovative solutions at scale, pushing the technological and science boundaries. You will guide the design, modeling, and architectural choices of state-of-the-art large language models and multimodal models. You will devise and implement new algorithms and new learning strategies and paradigms. You will be technically hands-on and drive the execution from ideation to productionization. You will work in collaborative environment with other technical and business leaders, to innovate on behalf of the customer.BASIC QUALIFICATIONS- Experience programming in Java, C++, Python or related language- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse- Master's degree or above in computer science, mathematics, statistics, machine learning or equivalent quantitative field- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning- Experience researching about machine learning, deep learning, NLP, computer vision, data science ...

The Prime Video Global App Experience organization operates at planet-wide scale and is a critical part of Prime Video’s flywheel. Our client apps (mobile, living room, desktop, automotive) are the gateway to the Prime Video experience, enabling customers to quickly find something to watch at which point the app fades in the background and the customer is immersed in the storytelling.We're reinventing how defects are detected in complex client apps, like Prime Video, and machine learning is going to be a key enabler to achieving that vision. The traditional approach of developing end-to-end integration tests on a per client basis isn't feasible at our global scale and large client distribution footprint. That approach to testing also doesn't detect "unknown/unknown" types of defects which occur more often than you'd expect when you operate a worldwide streaming video service used by hundreds of millions of customers. If you are passionate about film, sport or TV and you’re looking for a role where you can maximize your impact as a world class Principal Applied Scientist then come help us achieve our mission of building the most customer-centric, immersive and visually-rich video streaming experience on any device.Key job responsibilitiesAs a Principal Applied Scientist in the Prime Video Global App Experience organization you will leverage your deep subject matter expertise in applied machine learning to prototype and productionalize approaches to detect defects in our client apps. The space is ambiguous. No one is going to tell you which types of defects to work on nor which ML techniques to apply (classical ML, Deep Learning, CVML, NLP, etc) . Your role is to assess the opportunities, tailwinds, headwinds and risks. Then develop a vision and execute on a plan to achieve meaningful outcomes for our customers. At our scale improving CX metrics by just a few basis points can result in the reduction of millions of defects experienced by our customers annually. You will also work with external academic partners to support our in-house talent with direct access to cutting edge research and mentoring.BASIC QUALIFICATIONS- 10+ years of tech industry or equivalent experience- Experience working effectively with science, data processing, and software engineering teams- Graduate degree in Computer science/Math or related field.- Experience in building complex, real-time systems involving AI, ML, NLP with successful delivery to customers.- Demonstrated track record of project delivery for large, cross-functional projects with evolving requirements. Ability to take a project from requirements gathering and design to actual product launch- Computer Science fundamentals in data structures, algorithm design and complexity analysis.- Ability to develop a machine learning strategy for non-traditional areas such as developer productivity, software quality assurance (testing), availability, app performance/fluidity and latency reduction.- Exceptional customer relationship skills including the ability to discover the true requirements underlying feature requests, recommend alternative technical and business approaches, and lead science efforts to meet aggressive timelines with optimal solutions.- Demonstrated track record of peer-reviewed scientific publications that advance state-of-the art for applied science. ...

Amazon Supply Chain forms the backbone of the fastest growing e-commerce business in the world. The sheer growth of the business and the company's mission "to be Earth’s most customer-centric company” makes the customer fulfillment business bigger and more complex with each passing year.The EU SC Science Optimization team is looking for an exceptionally talented Scientist to tackle complex and ambiguous optimization and forecasting problems for our EU/NA fulfillment network.The team owns the optimization of our Supply Chain from our suppliers to our customers. We are also responsible for analyzing the performance of our Supply Chain end-to-end and deploying Operations Research, Machine Learning, Statistics and Econometrics models to improve decision making within our organization, including forecasting, planning and executing our network. We work closely with Supply Chain Optimization Technology (SCOT) teams, who own the systems and the inputs we rely on to plan our networks, the worldwide scientific community, and with our internal EU stakeholders within Supply Chain, Transportation, Store and Finance.We are looking for an experienced candidate having a well-rounded-technical/science background, with a particular expertise in stochastic optimization and probabilistic forecasting, as well as a history of delivering complex scientific projects end-to-end, and is comfortable in developing long term scientific solutions while ensuring the continuous delivery of incremental model improvements and results in an ever-changing operational environment.As an Applied Scientist, you will design, develop and deploy robust and scalable scientific solutions via Operations Research and Machine Learning algorithms, especially in the context of stochastic customer demand and other sources of uncertainty requiring to move past deterministic optimization. You will partner with other tech and science teams, operations, finance to identify opportunities to improve our processes in order to drive efficiency improvements in our Fulfillment Center network flows.This role requires a self-starter aptitude for independent initiative and the ability to influence partner scientific and operational teams so to drive innovation in supply chain planning and execution. You are passionate, results-oriented, and inventive scientist who obsesses over the quality of your solutions and their fast and scalable implementation to address and anticipate customer needs.Key job responsibilitiesBuild state-of-the art, robust and scalable Stochastic Optimization and Probabilistic Forecasting algorithms to drive optimal planning under uncertainty and execution in Amazon end-to-end supply chainDesign and engineer algorithms using Cloud-based state-of-the art software development techniquesThink multiple steps ahead and develop for long term solutions while continuously delivering incremental improvements to existing onesPrototype fast, ensure early adoption via pilots, integrate feedback into the models, and iterateOperationalize (i.e. deliver) your science solutions by closely partnering with internal customers, understand their needs/blockers and influence their roadmapLead complex analysis and clearly communicate results and recommendations to leadershipAct as an active member of the science community by researching, applying and publishing internally/externally the latest OR/ML techniques from both academia and industryBASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning- 3+ years of building models for business application experience- 2+ years experience with Stochastic Optimization techniques (e.g. Stochastic Linear Programming, Stochastic Dynamic Programming) and ML for Probabilistic Forecasting- Sharp analytical abilities, excellent written and verbal communication skills- Ability to handle ambiguity and fast-paced environment ...

We are seeking an Applied Scientist to join our AI Security team, which builds security tooling and paved path solutions to ensure Generative AI (GenAI) based experiences developed by Amazon uphold our high security standards, and uses AI to develop foundational services that make security mechanisms more effective and efficient.As an Applied Scientist, you’ll be responsible for designing and implementing state-of-the-art solutions, to build an AI-based foundational service for securing products and services at Amazon scale. You will collaborate with applied scientists and software engineers to develop innovative technologies to solve some of our hardest security problems, and AI-based security solutions that support builder teams across Amazon throughout their software development journey, enabling Amazon businesses to strengthen their security posture more efficiently and effectively.Key job responsibilities• design and implement accurate and scalable methods to solve our hardest AI security problems• Lead and partner with applied scientists and software development engineers to drive technical design and implementation for a foundational GenAI-based security serviceAbout the teamThe mission of the AI Security organization is to ensure Generative AI experiences delivered by Amazon to our customers uphold our high security standards and to harness AI to strengthen Amazon’s security posture more efficiently and effectively.A day in the lifeA day in the life involves meeting Vulnerability Management and Incident Responder teams to review data flows, prediction use cases, and automation gaps. From here you will research data sets, working with security/software engineers to retrieve data needed for your analysis and explorations. Once you have framed the problems, you will conduct experiments, regressions, and various analysis activities to find insights. You will develop and train models that will then be placed into a production environment with the help of software engineers. You will then work with your security team partners to understand the effectiveness of the models created.About the teamThe Defensive Security team is small, tight-knit, and located in Austin, Texas. It is primarily software engineers, but will be developed into a hybrid team of software engineers and security engineers. This team will have tenured Amazonian leadership, with a track record of mentoring, coaching, and career progression support.About Amazon SecurityDiverse Experiences — Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Why Amazon Security? — At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores.Inclusive Team Culture — In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices.Training & Career Growth — We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance — We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.BASIC QUALIFICATIONS- Advanced degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field- Knowledge of programming languages such as C/C++, Python, Java or Perl ...

The Campaign Measurement & Optimization (CMO) organization is looking for a Senior Applied Scientist interested in solving one of the most challenging business problems in marketing measurement and optimization, a thought leader with deep expertise in ML modeling, and scaling measurement science. Working with our team of data / research / applied scientists, economists, engineers, and product managers, this leader will help redefine marketing investment decision making at Amazon and its subsidiaries.The Campaign Measurement & Optimization (CMO) organization’s mission is to be the most trusted source of measurement science solutions to drive marketing investment decisions across Amazon. The CMO team provides incrementality and efficiency measurement services to the marketing stakeholders across Amazon’s lines of business, including Stores, Prime Video, Amazon Devices, Alexa, Amazon Business, Amazon Music, Amazon Fresh, as well as subsidiaries including Audible, Ring, Whole Foods, and more. CMO applies industry leading deep learning based causal inference models to measure omni-channel effectiveness of marketing campaigns from these businesses worldwide. The impact and influence of the organization is tremendous, helping optimize spend decisions on a scale that exceeds many countries’ GDP. Our outputs shape Amazon product and marketing teams’ decisions and therefore how Amazon customers see, use, and value their experience with Amazon.This is a high-impact role with opportunities to develop systems and analyze marketing effectiveness that contributes billions of dollars to the business. As a Senior Scientist in the team, you will be responsible for designing and developing cutting edge measurement and optimization models, while collaborating with businesses, marketers, and software teams to solve key challenges facing the teams. Such challenges include measuring the incremental impact of multi-billion $$ multi-channel marketing portfolios, developing Deep Learning models for estimating the impact on sparse customer actions, and scaling measurement solutions for WW marketplaces. Unlike many companies who buy existing off-the-shelf marketing measurement systems, we are responsible for studying, designing, and building systems to serve Amazon’s suite of businesses. Our team members have an opportunity to be on the forefront of marketing measurement thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, research scientists, economists and software developers in the business.In this role, you will be a technical leader in Marketing science research with significant scope, impact, and high visibility. You will champion cutting edge ML models using the latest methods in causal estimation and portfolio optimization. You will lead strategic measurement science initiatives in CMO and across various marketing teams, scaling experimentation and measurement science models, real-time inference, and cross-channel orchestration. As a successful scientist, you are an analytical problem solver who enjoys diving into data, leads development of new models, is excited about investigations and algorithms, and can credibly interface between technical teams and business stakeholders. You are an expert in employing deep learning models to solve business problems, preferably in causal inference. You are a hands-on innovator who can contribute to advancing Marketing measurement technology in a B2C and B2B environment, and push the limits on what’s scientifically possible with a razor sharp focus on measurable customer and business impact. You will coach and guide junior scientists to grow the team’s talent and scale the impact of your work.BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

This is a unique opportunity for a postdoc to work on research projects that investigate state of the art NLP, IR, and LLM approaches for understanding retail products and their pricing. This will include working with billion-scale datasets and investigating how the world knowledge captured by LLMs reflects real world prices, and investigating more advanced prompting and reasoning techniques to construct large knowledge graphs that are specialized for various pricing use cases such as probabilistic price estimation, as well as error detection and correction.Key job responsibilitiesIn this role you will:• Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community.• Publish your innovation in top-tier academic venues and hone your presentation skills.• Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise. About the teamThe retail pricing science team is a centralized diverse team of STEM scientists that develop statistical, ML, RL, optimization and economic models that drive pricing for products sold by Amazon worldwide, as well as monitoring of prices and experimentations in pricing. The team has a dual focus on competitiveness and long term financial optimality.BASIC QUALIFICATIONSBasic qualifications include: - PhD in a relevant field, received within 2 years of starting the program- Proven publication record in Operation Research, Management Science, Statistics, Machine Learning, Computer Science, Econ, or other related technical fields- Experience in data science and quantitative research- Proficiency in technologies relevant to the subfield ...

The Ads Measurement Science team in the Measurement, Ad Tech, and Data Science (MADS) team of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of their ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision.We are hiring an Economist on the team to develop the next generation of incrementality measurement products, capturing the effect of advertising in driving sales as well as the effects of measurement tools on advertiser engagement with Amazon. As an Economist on the team, you will lead the design, implementation, and validation of large-scale causal inference methodologies to capture these properties. You will communicate your results with science and business leaders, and partner with other scientists and engineers to carry solutions into production.Key job responsibilitiesLeverage deep expertise in causal inference to develop robust, causally grounded ads measurement solutionsDisambiguate problems to propose clear evaluation frameworks and success criteriaWork autonomously and write high quality technical documentsPartner closely with other scientists to deliver large, multi-faceted technical projectsShare and publish works with the broader scientific community through meetings and conferencesCommunicate clearly to both technical and non-technical audiences and leadersContribute new ideas that shape the direction of the team's workMentor more junior scientists and participate in the hiring processBASIC QUALIFICATIONS- PhD in economics or equivalent- Experience in data mining (SQL, ETL, data warehouse, etc.) and using databases in a business environment with large-scale, complex datasets- Experience in implementing modern machine-learning methods (e.g., boosted regression trees, random forests, neural networks)- Deep expertise in causal inference, with articles published in peer-reviewed econometrics journals.- Proficiency in Python or a related programming language. ...

Amazon’s eCommerce Foundation (eCF) organization provides the core technologies that drive and power Amazon's Stores, Digital, and Other (SDO) businesses. Millions of customer page views and orders per day are enabled by the systems eCF builds from the ground up. CloudTune, within eCF, empowers growth and business agility needs by automatically and efficiently managing AWS capacity and business processes needed to safely meet Amazon’s customer demand. CloudTune serves its primary customers, internal software teams, through forecast driven automation of cost controllership, capacity management and scaling. We predict expected load, and drive procurement and allocation of AWS capacity for new product launches and high velocity events like Prime Day and Cyber Monday. CloudTune, in partnership with Region Flexibility, is driving an SDO-wide program to diversify our use of AWS regions beyond DUB, IAD, and PDX regions. The objective of the Diversify AWS Region Usage (DARU) program is to mitigate the risk of capacity concentration by encouraging teams to design workloads that are region-flexible, utilize AWS automation such as Flexible Fleets to access multiple capacity pools, and optimize workload placement so SDO efficiently utilizes AWS. This is a strategic, highly visible, multi-year program which spans all Amazon business.CloudTune is looking for an experienced Applied Scientist to join our forecasting team and support DARU program. The team develops sophisticated algorithms that involve learning from large amounts of past data, such as actual sales, website traffic, merchandising activities, promotions, similar products and product attributes to forecast the demand for our compute infrastructure. These forecasts are used to determine the level of investment in capital expenditures, promotional activity, engineering efficiency projects and determining financial performance.As a Senior Scientist in CloudTune, you will work with other scientists, software engineers, data engineers, and product managers on a variety of important applied machine learning problems in the area of time series modeling. You will work on statistical problems with a high level of ambiguity. You will analyze and process large amounts of data, develop new algorithms and improve existing approaches based on statistical models, machine learning algorithms and big data solutions to automatically scale Amazon’s compute infrastructure, optimizing the balance between availability risk and cost efficiency for all of Amazon businesses.Key job responsibilities• Process and analyze large data sets, mining additional data sources as needed• Analyze compute scaling metrics to identify business drivers that influence infrastructure expenditures• Build statistical models and drive scalable solutions for multi-year capacity demand forecasting horizons• Prototype these models by using high-level modeling languages such as R or Python• Create, enhance, and maintain technical documentation, and present to other scientists and business leadersBASIC QUALIFICATIONS- 5+ years of building machine learning models for business application experience- PhD, or Master's degree and 7+ years of building machine learning models or developing algorithms for business application experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

Amazon's AGI Information team is seeking a passionate, talented, and inventive MLE to lead the development of industry-leading systems. As part of our cutting-edge team, you will play a pivotal role in reinventing efficient AI solutions at scale.In this role, you will work alongside renowned researchers and engineers to enable our customers to seamlessly interact with content. You will design, develop, and deploy scalable and efficient machine learning models and systems to power these transformative applications. The scope of these efforts includes defining public APIs, performance tuning and analysis, crafting and implementing compiler and optimization techniques for neural networks, and other general software engineering work.Key job responsibilities* Design and build scalable infrastructure that enables training, evaluating and deploying machine learning models* Design and develop tools for monitoring the performance of machine learning models at scale* Design and develop lineage and artifact tracking infrastructure* Design and develop reproducible ML Pipelines orchestrating various components for ML models.* Optimize model performance, robustness, and efficiency through techniques like model compression, knowledge distillation, and hardware acceleration* Embrace and champion engineering best practices within your group and beyond* Produce clean, high-quality code, tests, and written documentation* Mentor and guide junior engineers, share knowledge, and contribute to an innovative, collaborative cultureBASIC QUALIFICATIONS- 3+ years of non-internship professional software development experience- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience- Experience programming with at least one software programming language ...

The Automated Reasoning Group in AWS Cloud Operations is looking for an Applied Scientist to work on the intersection of Artificial Intelligence and program analysis to automate the management of cloud compute resources, with an initial view towards reactive, incident-driven remediation, and a longer-term view towards preventative action taken. You will be part of a larger organization that develops tooling for managing a full range of cloud resources with an application-centric view.Each day, hundreds of thousands of developers make billions of transactions worldwide on AWS. They harness the power of the cloud to enable innovative applications, websites, and businesses. Using automated reasoning technology and mathematical proofs, AWS allows customers to answer questions about security, availability, durability, and functional correctness. We call this provable security, absolute assurance in security of the cloud and in the cloud. https://aws.amazon.com/security/provable-security/About the teamYou will be working with a team of automated reasoning specialists as well as software development engineers. We develop automated tools and techniques for code synthesis and analysis.Why AWSAmazon 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.Utility Computing (UC)AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.Inclusive Team CultureHere 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.Work/Life BalanceWe 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.Mentorship and Career GrowthWe’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.Diverse ExperiencesAmazon 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.BASIC QUALIFICATIONS- PhD, or Master's degree- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing- 3+ years of building models for business application experience ...

We're looking for an experienced Applied Scientist with exceptional technical, analytical, and innovative capabilities to research, design, and create elegant machine learning solutions. Your solutions will help our advertisers with multi-media and multi-lingual advertising offerings, leveraging Generative AI, Deep Neural Networks, Natural Language Processing (NLP), and Computer Vision (CV). You will build ML models that localize multi-media advertising contents, including text, images and videos. You will also identify opportunities to leverage ML beyond localization, including, international expansion and global advertising. Your work will directly impact our customers in the form of products and services used directly by our advertisers as well as our third-party integrators.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 are strategically important to our businesses driving long term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!The Advertiser Growth Engine (AGE) team owns and builds services and applications across Amazon World-Wide Advertising that make advertising across countries/languages as easy as flipping a switch. We are focused on: (1) expanding Amazon Ads advertiser base, and (2) eliminating localization, operational, and marketplace knowledge gap barriers for Advertisers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth globally.Key job responsibilitiesAs an Applied Scientist on this team, you will:- Build and deliver end-to-end machine learning solutions; build ML models and perform data analysis to deliver scalable solutions to business problems.- Work closely with senior leaders across science, engineering, and product disciplines to drive the team's roadmap and establish business requirements. - Perform hands-on analysis and modeling with enormous data sets to develop insights that increase traffic monetization and merchandise sales without compromising shopper experience.- Run A/B experiments that affect hundreds of millions of customers, evaluate the impact of your optimizations and communicate your results to various business stakeholders.- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.- Research new innovate machine learning approaches.BASIC QUALIFICATIONS- 5+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

The Amazon AGI SF Lab is focused on developing new foundational capabilities for useful AI agents that can take actions in the digital and physical worlds. In other words, we’re enabling practical AI that can actually do things for us and make our customers more productive, empowered, and fulfilled. The lab is designed to empower AI researchers and engineers to make major breakthroughs with speed and focus toward this goal. Our philosophy combines the agility of a startup with the resources of Amazon. By keeping the team lean, we’re able to maximize the amount of compute per person. Each team in the lab has the autonomy to move fast and the commitment to pursue high-risk, high-payoff research.Key job responsibilities- Collaborate across AGI Autonomy to align team goals with the broader Autonomy research program- Identify and prioritize research opportunities to unlock the next set of agent capabilities- Mentor and guide team members to achieve their career goals and objectives- Other management activities, e.g., communicating with stakeholders, structuring work, and growing the teamBASIC QUALIFICATIONS- 5+ years of experience in formal management roles (i.e., with at least 3 direct reports)- Expertise in machine vision, autonomous systems, natural language processing, or related AI/ML field- Track record of successful projects in an applied research context ...

The Brand Experience (BX) organization creates, builds and leads innovation for Brand Owners in the Amazon store worldwide. Our growing portfolio of BX tools enable Brands to tell their unique Brand and product stories, optimize content through statistical experimentation, solicit and manage reviews to earn Customer trust and grow their business as well as engage with new and loyal Customers through a variety of channels.We are looking for a Applied Scientist to drive data insights and opportunities to improve Brands’ success. As a successful applied scientist on our talented team of scientists and engineers, you will solve complex problems to identify actionable opportunities, and collaborate with engineering, research, and business teams for future innovation. You need to be a sophisticated user and builder of statistical models and put them in production to answer specific business questions. You are an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. You will continue to contribute to the research community, by working with scientists across Amazon, as well as collaborating with academic researchers and publishing papers (www.aboutamazon.com/research).BASIC QUALIFICATIONS- 3+ years of building models for business application experience- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

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. This role is part of the foundations modeling team with focus on model pre-training across modalities. Key job responsibilitiesYou will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).BASIC QUALIFICATIONSPhD with specialization in artificial intelligence, natural language processing, machine learning, or computational cognitive science 10+ years of combined academic and research experience. Strong publication record in top-tier journals and conferences. Functional thought leader, sought after for key tech decisions. Can successfully sell ideas to an executive level decision maker. Mentors and trains the research scientist community on complex technical issues. Experience developing software in traditional programming languages (C++, Java, etc..). Excellent written and spoken communication skills ...

Do you want to be part of a team that's revolutionizing Amazon's fulfillment and packaging technology? Can you commit to optimizing systems that process tens-of-millions of customer packages daily with the lowest cost to serve and a defect-free customer experience? Do you have a passion for solving complex science challenges and building a sustainable e-commerce experience?Your statistical and machine learning skills can help make that a reality on the Mechatronics and Sustainable Packaging team. We are seeking a Principal Applied Scientist who will join a team of experts in the field of Statistics, Operational Research, Machine Learning (ML), Computer Vision and Generative AI to work together to break new ground in the world of automated packaging solutions. You'll work in a collaborative environment where you can pursue ambitious research with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. You'll see the work you do directly improve the packaging experience of Amazon customers in the fulfillment technology space. If you are interested in robotics, computer vision, machine learning, statistics, big data, and building scalable solutions, this role is for you.The successful candidate will have a PhD in Computer Science, Statistics, or Engineering with a strong focus on data analysis, machine learning, generative AI or a related field, and 10+ years of practical experience solving complex problems in computer vision, anomaly detection, robotics. or multi-modal classification systems. Manufacturing, packaging and/or logistic experience is a plus, but not a requirementKey job responsibilities- Advance exploratory research projects in machine learning, statistics and related fields to create defect-free packaging customer experiences- Analyze large amounts of Amazon shipments to discover patterns, find opportunities, and develop highly innovative, scalable algorithms to seize these opportunities- Validate new or improved models via statistically relevant experiments across millions of customers- Work closely with software engineering teams to build scalable prototypes for testing, and integrate successful models and algorithms in production systems at very large scaleBASIC QUALIFICATIONS-Ph.D. degree in Computer Science, Statistics, Machine Learning, or a related field with publications in refereed academic conferences and journals-10+ years of experience of solving difficult machine learning, optimization, or statistical business problems-Experience programming in Python, Java, C++ or a related language-Proven track in leading, mentoring, and growing teams of scientists -Demonstrated ability to serve as a technical lead -Excellent writing skills for presenting business cases and scientific models with rigorous analyses that support results/conclusions to influence important decisions. -Strong fundamentals in problem solving, algorithm design and complexity analysis ...