Machine Learning Science

The Geospatial science team solves problems at the interface of ML/AI and GIS for Amazon's last mile delivery programs. We have access to Earth-scale datasets and use them to solve challenging problems that affect hundreds of thousands of transporters. We are looking for strong candidates to join the transportation science team which owns time estimation, GPS trajectory learning, and sensor fusion from phone data.You will join a team of GIS and ML domain experts and be expected to develop ML models, present research results to stakeholders, and collaborate with SDEs to implement the models in production.Key job responsibilities- Understand business problems and translate them into science problems- Develop ML models- Present research results- Write and publish papers- Write production code- Collaborate with SDEs and other scientistsBASIC 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 ...

Are you seeking an environment where you can drive innovation? Do you want to be at the forefront of applying machine learning to solve real world problems? Do you want to play a key role in the future of Amazon's Stores business? Come and join us!The Supply Chain Optimization Technologies (SCOT) group is seeking a Principal Applied Scientist to join our Reinforcement Learning team. Our research team, which includes Sham Kakade and Dean Foster, has published research in top journals and conferences and has a significant impact on the field. Through the launch of several Deep RL models into production, our work also affects decision making in the real world.Key job responsibilitiesKey job responsibilities include:- Design, implement and evaluate models, agents and software prototypes- Technical leadership for a group of highly motivated and talented scientists- Engage key business stakeholders and scientists to surface opportunities for improvement and identify business requirements. - Work closely with partner teams to develop solutions to ambiguous business problems and integrate novel methodology into our team and business.- Work closely with senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community.- Raise the bar of scientific research by innovating and publishingAbout 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 Reinforcement Learning team is pioneering the application of reinforcement learning techniques for these applications. The team combines empirical research and real world testing, backed by a robust theoretical foundation. Some research publications include:- Deep Inventory Management [https://arxiv.org/abs/2210.03137, NeurIPS 2022 Workshop Presentation] - Learning an Inventory Control Policy with General Inventory Arrival Dynamics [https://arxiv.org/abs/2310.17168]- Meta-Analysis of Randomized Experiments with Applications to Heavy-Tailed Response Data [https://arxiv.org/abs/2112.07602]- What are the Statistical Limits of Offline RL with Linear Function Approximation? [https://arxiv.org/abs/2010.11895, NeurIPS 2021 Workshop Presentation]- A Study on the Calibration of In-context Learning [https://arxiv.org/abs/2312.04021]We encourage collaboration across teammates 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.BASIC QUALIFICATIONS- PhD in one of the following disciplines: Computer Science, Machine Learning, Statistics, Applied Math or a related quantitative field- 10+ years of relevant, broad research experience after PhD- Publications at top-tier peer-reviewed conferences or journals in one of these areas: reinforcement learning, deep learning, and machine learning- Fluency in Python, SQL or similar scripting languages and skilled at Java, C++, or other programing languages.- Strong algorithm development experience- Depth and breadth in state-of-the-art machine learning technologies- Strong prior experience with mentorship and/or management of senior scientists and engineers. ...

Do you want to create worldwide impact in robotics while solving challenges at the edge of robotics research? Our team in Amazon Robotics builds high-performance, real-time robotic systems that can perceive, learn, and act intelligently alongside humans—at Amazon scale. Our mission is to enable robots to interact safely, efficiently, and fluently with the clutter and uncertainty of real-world fulfillment centers. Our AI solutions enable robots to learn from their own experiences, from each other, and from humans to build intelligence that feeds itself.We hire and develop subject matter experts in AI with a focus on computer vision, deep learning, intelligent control, semi-supervised and unsupervised learning. We target high-impact algorithmic unlocks in areas such as scene and activity understanding, simultaneous localization and mapping, closed-loop control, robotic grasping and manipulation—all of which have high-value impact for our current and future fulfillment networks.We are seeking an exceptional Principal Applied Scientist to join our organization, who possesses a deep understanding of both classical computer vision techniques and state-of-the-art machine learning approaches. The ideal candidate will be hands-on, coding-proficient, and a thought leader capable of influencing the direction of ML applied to Perception and Robotics.Key qualifications:* Extensive experience in computer vision, from traditional methods (e.g., SIFT, SURF, optical flow) to modern deep learning architectures* Profound understanding of advanced vision models such as Vision Transformers (ViTs), MultiMAE, and their applications* Expertise in generative models, particularly diffusion models and their applications in robotics (e.g., diffusion policy)* Proven track record in developing scalable ML frameworks for online/offline learning, large language models, prediction systems, and continuous model optimization* Strong background in 3D vision, including multi-view geometry, SLAM and 3D reconstructionKey job responsibilities* Set the technical direction for the group, bridging classical computer vision techniques with cutting-edge deep learning approaches* Drive research and development of advanced perception systems, incorporating the latest advancements in self-supervised and multi-modal learning* Collaborate with top-notch scientists and engineers to deliver the world's most scalable and robust robotic systems* Lead the integration of vision-language models and foundation models into perception pipelines* Develop novel approaches for few-shot learning and domain adaptation in robotic perception* Advance the state-of-the-art in areas such as 3D scene understanding, object pose estimation, and activity recognition* Drive ideas to products using a comprehensive toolset including deep learning, active learning, and computer vision (camera selection, camera calibration, instance and semantic segmentation, pose estimation, activity understanding)* Mentor and guide team members in adopting best practices and staying current with rapid advancements in the fieldThe ideal candidate will have a Ph.D. in Computer Science, Electrical Engineering, or a related field, with a strong publication record in top-tier conferences (CVPR, ICCV, NeurIPS, ICML, etc.) and practical experience applying advanced ML techniques to real-world robotics problems.A day in the lifeAmazon offers a full range of benefits for you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!About the teamBASIC QUALIFICATIONS- 10+ years of scientist or machine learning engineer management experience- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field- Experience building state of the art machine learning models or developing algorithms ...

Take Earth's most customer-centric company. Mix in hundreds of millions of shoppers spending tens of billions of dollars annually, an exciting opportunity to build next-generation shopping experiences, Amazon’s tremendous computational resources, and our extensive e-Commerce experience. What do you get? The most exciting position in the industry.About our organization: Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. We run global experiments and our work has revolutionized e-commerce with features such as "Keep shopping for", "Tap to explore", “Customers who bought this item also bought”, and “Frequently bought together” among others. Amazon’s internal surveys regularly recognize us as one of the best engineering organizations to work for in the company, with visible high-impact work, low operational load, respectful work-life balance, and continual opportunity to learn and grow.You will play a critical role in ideation for the team. We are building the next generation ML systems that powers the biggest shopping engine on earth, and we hope you will join us!Key job responsibilitiesAs an Applied Scientist on the team you will be working on cutting edge ways to help customers find the right products and content on their shopping journey. Our goal is to help customers achieve their objective seamlessly while shopping on Amazon. We are investing in multiple fronts including but not limited to GenerativeAI, LLMs, transformers, sequence models, reinforcement learning. This is an opportunity to come in on Day0 and influence the science roadmap of one of the most interesting problem spaces at Amazon - understanding the Amazon customer to build deeply personalized and adaptive shopping experiences. We will be working on applying cutting edge science and research into production to elevate the customer experience. You will be part of a multidisciplinary team, working on one of the largest scale machine learning systems in the company. You will hone your skills in areas such as deep learning and reinforcement learning while building scalable industrial systems. As a member of a highly leveraged team of talented engineers and ML scientists, you will have a unique opportunity to help build infrastructure that accesses petabytes of data to produce and deliver models that deliver state of the art customer experiences. About the teamOur mission is to delight every Amazon customer with a consistent and adaptive personalized shopping experience. We achieve our mission through investments in large scale machine learning, distributed systems and user experience with the purpose of delivering the future of shopping on Amazon. 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 ...

Amazon is hiring a Principal Applied Scientist (PAS) to join the Search and Conversational Shopping AI team. In this role, you will be responsible for the architectural design and technological advancements of the customer experience of Amazon Rufus, our next-generation, AI-driven search and shopping assistant. This innovative role focuses on developing innovative search and shopping experiences, utilizing large language models, generative AI, and advanced machine learning technologies.Key job responsibilitiesAs a Principal Applied Scientist in Search, you will possess deep expertise in machine learning and data science, with specializations in information retrieval, recommendations, ranking, large language models, and generative AI across various modalities. The role involves solution alignment across multiple partners, such as front-end, relevance, ranking, and personalization teams. You will collaborate with teams of scientists and engineers to translate business and functional requirements into concrete deliverables, leading strategic efforts to enhance upper funnel search customer experiences. You will design integrated solutions efficiently delivered across all contributing stakeholder teams, driving alignment among these tech teams in the short term and influencing their future roadmaps in the long term to support our experimentation roadmap. Responsible for overall solution quality, this role will focus on improving experimentation velocity and, in the future, facilitating partner development on upper funnel customer experiences. This role ensures we are building scalable solutions with smart checks on data quality centrally, navigating the ambiguity inherent in this new area. You will make critical judgements to select the best technical solutions for both short and long-term experimentation objectives, bringing clarity from ambiguity, structuring tradeoff decisions, and effectively communicating on technically contentious topics. Finally, you will engage with academic partners to augment our in-house talent with access to the latest research and expert mentoring.About the teamThe vision of the Search and Conversational Shopping AI Team is to revolutionize the search and shopping experience through technological innovations in advanced AI and machine learning. We focus on enhancing query understanding, navigational and upper funnel search, developing LLM-based AI assistants, and more. Our goal is to create intuitive, personalized search interfaces that seamlessly connect customers with products, enhancing satisfaction, engagement, and transforming e-commerce interactions.BASIC QUALIFICATIONS1. Graduate degree in Computer Science, Math, or a related field.2. Experience in developing AI, ML, and NLP systems, with a proven ability to deliver projects successfully.3. Skilled in managing large, cross-functional projects with evolving requirements from start to finish.4. Strong foundations in data structures, algorithm design, and complexity analysis.5. Ability to strategize for ML platforms focusing on recommender systems, ranking, and customer interaction features.6. Exceptional ability to understand customer needs, propose alternative technical and business solutions, and deliver on tight deadlines.7. Record of peer-reviewed scientific publications in applied science. ...

We are seeking a passionate, talented, and inventive individual to join the Applied AI team and help build industry-leading technologies that customers will love. This team offers a unique opportunity to make a significant impact on the customer experience and contribute to the design, architecture, and implementation of a cutting-edge product. The mission of the Applied AI team is to enable organizations within Worldwide Amazon.com Stores to accelerate the adoption of AI technologies across various parts of our business. We are looking for a Senior Applied Scientist to join our Applied AI team to work on LLM-based solutions. We are seeking an experienced Scientist who combines superb technical, research, analytical and leadership capabilities with a demonstrated ability to get the right things done quickly and effectively. This person must be comfortable working with a team of top-notch developers and collaborating with our research teams. We’re looking for someone who innovates, and loves solving hard problems. You will be expected to have an established background in building highly scalable systems and system design, excellent project management skills, great communication skills, and a motivation to achieve results in a fast-paced environment. You should be somebody who enjoys working on complex problems, is customer-centric, and feels strongly about building good software as well as making that software achieve its operational goals. Key job responsibilitiesYou will be responsible for developing and maintaining the systems and tools that enable us to accelerate knowledge operations and work in the intersection of Science and Engineering. A day in the lifeOn our team you will push the boundaries of ML and Generative AI techniques to scale the inputs for hundreds of billions of dollars of annual revenue for our eCommerce business. If you have a passion for AI technologies, a drive to innovate and a desire to make a meaningful impact, we invite you to become a valued member of our team. BASIC QUALIFICATIONS 7+ years of building machine learning models for business application experience PhD, or Master's degree and 6+ years of applied research experienceExperience programming in Java, C++, Python or related languageExperience with large language models and their architectures, and deep learning ...

The Artificial General Intelligence (AGI) Information team is looking for a passionate, and talented Senior Applied Scientist with a strong experience in cutting-edge LLM technologies. In this role, you will innovate in the fastest-moving fields of current AI research, in particular in how to integrate a broad range of structured and unstructured information into AI systems (e.g. with RAG techniques), and you will get to immediately apply your results in highly visible Amazon products.If you are deeply familiar with LLMs, natural language processing, and machine learning and have experience working in high-performing research teams, this may be the right opportunity for you. Our fast-paced environment requires a high degree of independence in making decisions and driving ambitious research agendas all the way to production. You will work with other science and engineering teams as well as business stakeholders to maximize the velocity and impact of your contributions.Key job responsibilities- Leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in generative artificial intelligence (GenAI).- Work with talented peers to lead the development of novel algorithms and modeling techniques to advance the state of the art with LLMs.- Collaborate with other science and engineering teams as well as business stakeholders to maximize the velocity and impact of your contributions. About the teamIt's an exciting time to be a leader in AI research. In Amazon's AGI Information team, you can make your mark by improving information-driven experiences of Amazon customers worldwide. Your work will directly impact our customers in the form of products and services that make use of language and multimodal technology!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 ...

Do you want to join an innovative team of scientists who use machine learning and statistical techniques 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 help manage the trust and safety of millions of customer every day? Are you excited by the prospect of analyzing and modeling terabytes of data and create state-of-art algorithms to solve real world problems? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Amazon Account Integrity team.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- Communication and data presentation skills- Problem solving ability ...

Amazon.com strives to be Earth's most customer-centric company where people can find and discover anything they want to buy online. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Are you seeking an environment where you can drive innovation? Do you want to apply learning techniques and advanced mathematical modeling to solve real world problems? Do you want to play a key role in the future of Amazon's Retail business? This job for you! The Customer Behavior Analytics (CBA) team at Amazon is responsible for the architecture, design, implementation of tools used to understand customer behavior and value generation for all Amazon programs. Come and join us!Amazon’s CBA team is looking for Applied Scientists, who can work at the intersection of machine learning, statistics and economics; and leverage the power of big data to solve complex problems like long-term causal effect estimation.As an applied scientist, you will bring statistical modeling and machine learning advancements to analyze data and develop customer-facing solutions in complex industrial settings. You will be working in a fast-paced, cross-disciplinary team of researchers who are leaders in the field. You will take on challenging problems, distill real requirements, and then deliver solutions that either leverage existing academic and industrial research, or utilize your own out-of-the-box pragmatic thinking. This role requires a pragmatic technical leader comfortable with ambiguity, capable of summarizing complex data and models through clear visual and written explanations. The ideal candidate will have experience with machine learning models and causal inference. Additionally, we are seeking candidates with strong rigor in applied sciences and engineering, creativity, curiosity, and great judgment.Key job responsibilities- Understand and mine the large amount of data, prototype and implement new learning algorithms and prediction techniques to improve long-term causal estimation approaches.- Collaborate with product managers and engineering teams to design and implement solutions for Amazon problems- Design, build, and deploy effective and innovative ML solutions to improve various components of our ML and causal inference pipelines- Publish and present your work at internal and external scientific venues in the fields of ML and causal inference.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Knowledge of programming languages such as C/C++, Python, Java or Perl- Experience building machine learning models or developing algorithms for business application- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Have you ever wondered how Amazon predicts when your order will arrive and how we ensure that it actually arrives on at the promised date/time? Have you wondered where all those Amazon semi-trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? Does the idea of having worldwide impact on Amazon's logistics network including our planes, trucks, and vans sound exciting to you? If so, then we want to talk with you! At Amazon's Supply Chain Optimization Technologies (SCOT), we are tasked with optimizing the fulfilment on customer orders so that we fulfil all orders worldwide in the most intelligent manner while ensuring Amazon customers get their orders on time.Amazon Fulfillment Planning & Execution (FPX) Science team within SCOT- Fulfilment Optimization group is seeking Manager Research Science with expertise in Machine Learning and/or Optimization and a proven record of leading scientists and solving business problems through scalable ML solutions. FPX Science tackles some of the most mathematically complex challenges in transportation planning and execution space to improve Amazon's operational efficiency worldwide. We own Amazon’s global fulfilment center and transportation planning and execution. The team also owns the short-term network planning and execution that determines the optimal flow of customer orders through Amazon fulfilment network. This includes developing sophisticated math models and controllers that assign orders to fulfilment centers to be picked and packed and then planning the optimal ship method in terms of cost, speed and carbon impact to deliver to the customer. These plans drive downstream decisions that are in the billions of dollars at Amazon Scale worldwide. The systems we build are entirely in-house, and are on the cutting edge of both academic and applied research in large scale supply chain planning, optimization, machine learning and statistics. These systems operate at various scales, from real-time decision system that completes thousands of transactions per seconds, to large scale distributed system that optimize Amazon’s fulfilment network. As Amazon continues to build and expand the first party delivery network, this role will be critical to realize this vision. Your team and tech solution will have large impacts to the physical supply chain of Amazon, and play a key role in improving Amazon consumer business’s long-term profitability. If you are interested in diving into a multi-discipline, high impact space this is the team for you. We’re looking for a passionate, results-oriented, and inventive Scientist who can lead from the front towards developing and deploying ML models for our outbound transportation planning systems. In addition, you will be working on design, development and evaluation of highly innovative ML models for solving complex business problems in the area of outbound transportation planning systems. The position is located at Bellevue, WA, just next to Seattle with beautiful outdoors and great city life.Watch http://bit.ly/amazon-scot to get the big picture. Key job responsibilitiesAs a Manager of Research Science within FPX Science team, you will lead a team of research and applied scientists towards designing and deploy solutions that will likely draw from a range of scientific areas such as supervised, semi-supervised and unsupervised learning, reinforcement learning, advanced statistical modeling, and graph models. You will have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry, with some of the best product managers, research scientists, statisticians, and software engineers to integrate scientific work into production systems. You will bring deep technical expertise in the area of Machine Learning, and will play an integral part in building Amazon's Fulfillment Optimization systems. Other responsibilities include:* Lead a team of research and applied scientists towards design, development and evaluation of highly innovative ML models for solving complex business problems. * Technically lead and mentor the scientists on the team.* Research and apply the latest ML techniques and best practices from both academia and industry. * Use and analytical techniques to create scalable solutions for business problems. * Work closely with software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale. * Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.A day in the lifeIn this critical role, you will be a technical leader in operations research or machine learning with significant scope, impact, and visibility. Your solutions have the potential to drive billions of dollars in impact for Amazon's supply chain globally. As a science manager on the team, you will engage in all facets of the process from ideation, business analysis and scientific research to development and deployment of advanced models. We are seeking someone who wants to lead projects that require innovative thinking and deep technical problem-solving skills to create production-ready machine learning solutions. A successful candidate is able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. We look for individuals who know how to deliver results and show a desire to develop themselves, their team, and their career.About the teamFulfillment Planning & Execution Science team contains a group of scientists with different technical backgrounds including Machine Learning and Operations Research, who will collaborate closely with you on your projects. Our team directly supports critical functional areas across Fulfillment Optimization and the research needs of the corresponding product and engineering teams. We tackle some of the most mathematically complex challenges in facility and transportation planning and execution to improve Amazon's operational efficiency worldwide and at a scale that is unique to Amazon. We often seek the opportunity of applying hybrid techniques in the space of Operations Research and Machine Learning to tackle some of our biggest technical challenges. We disambiguate complex supply chain problems and create ML and optimization solutions to solve those problems at scale.BASIC QUALIFICATIONS- Ph.D. in Computer Science, Operations Research, Operations Management, Industrial Engineering, Statistics, Applied Mathematics, or a related field- 5+ years of hands-on experience in building machine learning models in business environment- Proven track in leading and mentoring scientists with demonstrated ability to serve as a technical lead- Strong fundamentals in problem solving, algorithm design and complexity analysis- Excellent communication skills, both written and oral catered appropriately towards both technical and business people.- Demonstrated ability to document the models and analysis and present the results/conclusions in order to influence business critical decisions ...

Come and be part of the International Seller Services (ISS) Central Analytics Data Engineering (DE) team and work on solving cutting edge GenAI solutions!We are a team of DEs who support Applied Scientists, Data Scientist, and Economists who experiment, research, and turn machine/deep learning and AI research into great products for our customers.ISS is seeking a smart, highly-motivated, and experienced ML Engineer to join our team. In this role, you'll help us create the right Data and ML infrastructure.As a ML Data Engineer, you will provide technical expertise, lead ML engineering initiatives and build end-to-end analytical solutions that are highly available, scalable, stable, secure, and cost-effective. You carry projects from proof-of-concept to deployment and serving with a high standard for model maintenance and operations. You orchestrate complex and/or distributed modeling systems to unlock new ML capabilities for your customers.You are passionate about working with huge unstructured and structured datasets and have experience with the organization and curation of data for analytics and model training. You have a strategic and long term view on architecting advanced data eco systems.You are experienced in building efficient and scalable data services and have the ability to integrate data systems with AWS tools and services to support a variety of customer use cases/applications.You will have the opportunity to work with scalable model development tools using SageMaker, AWS, and Docker. You will bring in techniques for automating model training, evaluation, deployment and monitoring using machine learning pipelines. You will work closely with researchers in building algorithms ranging from classical machine learning to state-of-the-art deep neural network models on diverse types of signals.Key job responsibilitiesIn this role, you have the opportunity to:- Design, implement and operate large-scale, high-volume, high-performance data structures for analytics and data science.- Develop and deploy models and pipelines that scale- Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.- Collaborate with Applied Scientists, Data Scientists, Data engineers to help adopt best practices in ML system creation, Experimentation Setup and documentation- Identify opportunities in existing data/ML solutions for improvementsExample projects:- Setting up a Dev environment for experimenting multiple embedding models for RAG setup-Implement a robust experimentation platform to test, iterate, and optimize the Conversation Assistants' performance across key RAG metrics- Developing reusable cloud infrastructure and deployment patterns to accelerate productionalization- Integrating disparate ML solutions into cohesive customer experiencesBASIC QUALIFICATIONSExperience with machine learning techniques such as pre-processing data, training and evaluation of classification and regression models, and statistical evaluation of experimental data.2+ years of non-internship professional ML-software development experienceProgramming experience with at least one modern language such as Python,Java, C++, or C# including object-oriented design2+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.Experience in building production quality and large scale deployment of applications related to NLP and ML ...

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and innovative applied scientist with a strong background in deep learning, to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems.Key job responsibilitiesAs an Applied Scientist with the AGI team, you will work with world-class scientists and engineers to develop novel data, modeling and engineering solutions to support the responsible AI initiatives at AGI. Your work will directly impact our customers in the form of products and services that make use of audio technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in AGI in speech/audio/music domains.About the teamOur team has a mission to push the envelope of AGI in speech/audio/music domains, in order to provide the best-possible experience for our customers.BASIC QUALIFICATIONS- PhD, or Master's degree and 2+ years of CS, CE, ML or related field experience- 1+ years of building models for business application experience- Experience programming in Java, C++, Python or related language- Experience with deep learning techniques- Experience with LLM model training and fine-tuning ...

Amazon is looking for world class scientists to join its AWS Fundamental Research Team working within a variety of machine learning disciplines. This group is entrusted with developing core machine learning solutions for AWS services. At the AWS Fundamental Research Team you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and explore conceptually large scale ML solutions across different domains and computation platforms. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists.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.About the teamDiverse ExperiencesAWS 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 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 U.S. Amazon offices.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 ...

Come be a part of a rapidly expanding $35 billion dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential.Key job responsibilitiesWe are seeking an Applied Scientist who has a solid background in applied Machine Learning and Data Science, deep passion for building data-driven products, ability to formulate data insights and scientific vision, and has a proven track record of executing complex projects and delivering business impact. Specific responsibilities include: • Data driven insights to accelerate acquisition of new members. • Grow benefits adoption based on customer segment, vertical, and drive customers to their "aha moment". • Work closely with software engineering teams to drive model implementations and new feature creations. • Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation • Advance team's engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner. About the teamThe Marketing Science team applies scientific methods and research techniques to enhance our understanding of AB consumer behavior, market trends, and the effectiveness of marketing strategies. Our goal is to develop and advance theories and models that can be used to make informed decisions in marketing and to provide insights into consumer decision-making processes. Additionally, we seek to identify and explore emerging trends and technologies in marketing, and to develop innovative approaches for addressing the challenges and opportunities in the field.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 in computer science, mathematics, statistics, machine learning or equivalent quantitative field- Experience building machine learning models or developing algorithms for business application ...

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth.The Search Ranking and Interleaving (R&I) team within the Marketplace Intelligence org in SP is responsible for determining which ads to show in Amazon search, where to place them, how many ads to place, and to which customers. This helps shoppers discover new products while helping advertisers put their products in front of the right customers, aligning shoppers’, advertisers’, and Amazon’s interests. To do this, we apply a broad range of machine learning, causal inference, and optimization techniques to continuously explore, learn, and optimize the ranking and allocation of ads on the search page. We are an interdisciplinary team with a focus on customer obsession and inventing and simplifying. Our primary focus is on improving the SP experience in search by gaining a deep understanding of shopper pain points and developing new innovative solutions to address them.We are looking for an Applied Scientist to join the Search Ranking team in MI. The team is responsible for improving the quality of ads shown to users (e.g., relevance, personalized and contextualized ranking to improve shopper experience and business metrics) via online experimentation, ML modeling, simulation, and online feedback. As an Applied Scientist on this team, you will identify big opportunities for the team to make a direct impact on customers and the search experience. You will work closely with with search and retail partner teams, software engineers and product managers to build scalable real-time ML solutions. You will have the opportunity to design, run, and analyze A/B experiments that improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact while broadening your technical skillset. Key job responsibilities- Tackle and solve challenging science and business problems that balance the interests of advertisers, shoppers, and Amazon.- Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.- Develop real-time machine learning algorithms to allocate billions of ads per day in advertising auctions.- Develop efficient algorithms for multi-objective optimization using deep learning methods to find operating points for the ad marketplace then evolve them- Research new and innovative machine learning approaches.BASIC QUALIFICATIONS- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field- Experience programming in Java, C++, Python or related language- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse ...

Alexa is the voice activated digital assistant powering devices like Amazon Echo, Echo Dot, Echo Show, and Fire TV, which are at the forefront of this latest technology wave. To preserve our customers’ experience and trust, the Alexa Sensitive Content Intelligence (ASCI) team creates policies and builds services and tools through Machine Learning techniques to detect and mitigate sensitive content across Alexa. We are looking for an experienced Senior Applied Scientist to build industry-leading technologies in attribute extraction and sensitive content detection across all languages and countries.An Applied Scientist will be a tech lead for a team of exceptional scientists to develop novel algorithms and modeling techniques to advance the state of the art in NLP or CV related tasks. You will work in a hybrid, fast-paced organization where scientists, engineers, and product managers work together to build customer facing experiences. You will collaborate with and mentor other scientists to raise the bar of scientific research in Amazon. Your work will directly impact our customers in the form of products and services that make use of speech, language, and computer vision technologies.We are looking for a leader with strong technical expertise and a passion for developing science-driven solutions in a fast-paced environment. The ideal candidate will have a solid understanding of state of the art NLP, Generative AI, LLM fine-tuning, alignment, prompt engineering, benchmarking solutions, or CV and Multi-modal models, e.g., Vision Language Models (VLM), zero-shot, few-shot, and semi-supervised learning paradigms, with the ability to apply these technologies to diverse business challenges. You will leverage your deep technical knowledge, a strong foundation in machine learning and AI, and hands-on experience in building large-scale distributed systems to deliver reliable, scalable, and high-performance products. In addition to your technical expertise, you must have excellent communication skills and the ability to influence and collaborate effectively with key stakeholders.You will be joining a select group of people making history producing one of the most highly rated products in Amazon's history, so if you are looking for a challenging and innovative role where you can solve important problems while growing as a leader, this may be the place for you.Key job responsibilitiesYou'll lead the science solution design, run experiments, research new algorithms, and find new ways of optimizing customer experience. You set examples for the team on good science practice and standards. Besides theoretical analysis and innovation, you will work closely with talented engineers and ML scientists to put your algorithms and models into practice. Your work will directly impact the trust customers place in Alexa, globally. You contribute directly to our growth by hiring smart and motivated Scientists to establish teams that can deliver swiftly and predictably, adjusting in an agile fashion to deliver what our customers need.A day in the lifeYou will be working with a group of talented scientists on researching algorithm and running experiments to test scientific proposal/solutions to improve our sensitive contents detection and mitigation. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, and model development. You will mentor other scientists, review and guide their work, help develop roadmaps for the team. You work closely with partner teams across Alexa to deliver platform features that require cross-team leadership.About the hiring groupAbout the teamThe mission of the Alexa Sensitive Content Intelligence (ASCI) team is to (1) minimize negative surprises to customers caused by sensitive content, (2) detect and prevent potential brand-damaging interactions, and (3) build customer trust through appropriate interactions on sensitive topics.The term “sensitive content” includes within its scope a wide range of categories of content such as offensive content (e.g., hate speech, racist speech), profanity, content that is suitable only for certain age groups, politically polarizing content, and religiously polarizing content. The term “content” refers to any material that is exposed to customers by Alexa (including both 1P and 3P experiences) and includes text, speech, audio, and video.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 ...

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!SB ResponseModel team's role is to support the prediction of Click Through Rates, View Rates, and Conversion Rates for Sponsored Brands. Our goal is to enhance advertising efficiency, improve the shopper experience, and promote SB product recognition. We collaborate with different teams across the Amazon Ads to build scalable online and offline ML infrastructure systems to accelerate science innovations, facilitate business growth and promote technology innovation.As an Applied Scientist on this team, you will:- Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.- Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.- Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.- Run A/B experiments, gather data, and perform statistical analysis.- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.- Research new and innovative machine learning approaches.- Recruit Applied Scientists to the team and provide mentorship.Impact and Career GrowthYou 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 fundamentally 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.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 ...

The Amazon Devices & Services Demand Planning and Product Development (DePD) team is seeking an outstanding scientist with strong analytical and communication skills to help with demand forecasting and supply optimization for the entire Amazon device family of products, services and accessories. Amazon Devices represents a highly complex space with 100+ products across several product categories (e-readers [Kindle], tablets [Fire Tablets], smart speakers and audio assistants [Echo], wifi routers [eero], and video doorbells and cameras [Ring and Blink]), for sale both online and in offline retailers globally.We develop scalable and robust state-of-the-art data/analytics/ML and automation solutions that involve learning from different data sources and advanced descriptive, diagnostic, predictive prescriptive and cognitive models. With better forecasts, we drive down supply chain costs, enabling the offer of lower prices and better in-stock selection for our customers.In this role, you will have an opportunity to both develop advanced scientific solutions, and drive critical customer and business impact. You will play a key role to drive end-to-end solutions from understanding our business requirements, exploring a large amount of historical data and ML models, building prototypes and exploring conceptually new solutions, to working with partner teams for prod deployment. You will collaborate closely with scientists, engineering peers as well as business stakeholders. You will be at the heart of a growing and exciting focus area for Amazon Devices and Services.We are looking for an individual with outstanding analytical abilities, excellent communication skills, and someone who is comfortable working with cross-functional teams and systems. You will be responsible for researching, prototyping, experimenting, analyzing predictive models and developing smart automation solutions.Key job responsibilities· Research and develop new methodologies for demand forecasting, alarms, alerts and automation with advanced models and methods.· Build and maintain codebase, upholding engineering best practices · Improve upon existing methodologies by adding new data sources and implementing model enhancements.· Drive scalable and hands-off-the-wheel solutions.· Create and track accuracy and performance metrics (both technical and business metrics).· Create, enhance, and maintain technical documentation, and present to other scientists, engineers and business leaders.· Drive best practices on the team; mentor and guide junior members to achieve their career growth potential.About the teamThe team is a focused science team with Data and Applied Scientists looking for help with validating the technical decisions we are making and figuring out how to best solve our internal and partner’s needs. We have access to a growing science community within the org and partner with Engineering role on a daily basis.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 ...

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- 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 ...

Have you ever wondered how Amazon predicts when your order will arrive and how we ensure that it actually arrives on at the promised date/time? Have you wondered where all those Amazon semi-trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? Does the idea of having worldwide impact on Amazon's logistics network including our planes, trucks, and vans sound exciting to you? If so, then we want to talk with you! At Amazon's Supply Chain Optimization Technologies (SCOT), we are tasked with optimizing the fulfilment on customer orders so that we fulfil all orders worldwide in the most intelligent manner while ensuring Amazon customers get their orders on time.Amazon Fulfillment Planning & Execution (FPX) Science team within SCOT- Fulfilment Optimization group is seeking a Senior Applied Scientist with expertise in Optimization and a proven record of solving business problems through scalable Optimization solutions. FPX Science tackles some of the most mathematically complex challenges in transportation planning and execution space to improve Amazon's operational efficiency worldwide. We own Amazon’s global fulfilment planning and execution. The team also owns the short and mid-term-term network planning and execution that determines the optimal flow of customer orders through Amazon fulfilment network. This includes developing sophisticated math models and controllers that assign orders to fulfilment centres to be picked and packed and then planning the optimal ship method in terms of cost, speed and carbon impact to deliver to the customer. These plans drive downstream decisions that are in the billions of dollars at Amazon Scale worldwide! The systems we build are entirely in-house, and are on the cutting edge of both academic and applied research in large scale supply chain planning, optimization, machine learning and statistics. These systems operate at various scales, from real-time decision system that completes thousands of transactions per seconds, to large scale distributed system that optimize Amazon’s fulfilment network. As Amazon continues to build and expand the first party delivery network, this role will be critical to realize this vision. Your tech solution will have large impacts to the physical supply chain of Amazon, and play a key role in improving Amazon consumer business’s long-term profitability. If you are interested in diving into a multi-discipline, high impact space this is the team for you. We’re looking for a passionate, results-oriented, and inventive Senior Applied Scientist who can create and improve optimization models for our outbound transportation planning and execution systems. In addition, you will be working on design, development and evaluation of highly innovative Optimization models for solving complex business problems in the area of outbound transportation planning systems. Watch http://bit.ly/amazon-scot to get the big picture. Key job responsibilitiesAs a Senior Applied Scientist within FPX Science team, you will propose and deploy solutions that will likely draw from a range of scientific areas such as Optimization, machine learning, advanced statistical modeling, and graph models. You will have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry, with some of the best product managers, research scientists, statisticians, and software engineers to integrate scientific work into production systems. You will bring deep technical expertise in the area of Optimization, and will play an integral part in building Amazon's Fulfillment Optimization systems. Other responsibilities include:* Design, development and evaluation of highly innovative Math models for solving complex business problems. * Research and apply the latest Optimization techniques and best practices from both academia and industry. * Think about customers and how to improve the customer delivery experience. * Use and analytical techniques to create scalable solutions for business problems. * Work closely with software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale. * Technically lead and mentor other scientists in team. * Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.A day in the lifeThis is a great role for someone who likes to learn new things. You will have the opportunity to learn all about how Amazon plans for and executes within its logistics network including Fulfillment Centres, Air Stations, Sort Centres, Delivery Stations, and more. You will need to meet with many internal customers to understand their business and their challenges as you develop an effective solution to enable us to collectively scale. Our leadership is very interested in this effort so you will find lots of opportunities to get your ideas and plans in front of them for evaluation and alignment. We are seeking someone who wants to lead projects that require innovative thinking and deep technical problem-solving skills to create production-ready mathematical optimization solutions. A successful candidate is able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career.About the teamFulfillment Planning & Execution Science team contains a group of scientists with different technical backgrounds including Machine Learning and Operations Research, who will collaborate closely with you on your projects. Our team directly supports critical functional areas across Fulfillment Optimization and the research needs of the corresponding product and engineering teams. We tackle some of the most mathematically complex challenges in facility and transportation planning and execution to improve Amazon's operational efficiency worldwide and at a scale that is unique to Amazon. We often seek the opportunity of applying hybrid techniques in the space of Operations Research and Machine Learning to tackle some of our biggest technical challenges. We disambiguate complex supply chain problems and create ML and optimization solutions to solve those problems at scale.BASIC QUALIFICATIONS- 5+ years of applied research experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- 5+ years of industry or academic research experience- Ph.D. in Operations Research, Computer Science, Industrial Engineering, Statistics, Applied Mathematics, or a related field- 5+ years of hands-on experience in building optimization models in business environment- Proven track in leading and mentoring scientists with demonstrated ability to serve as a technical lead- Strong fundamentals in problem solving, algorithm design and complexity analysis ...