Machine Learning Science

Amazon's Next Generation Developer Experience (NGDE) Organization is looking for world class scientists and engineers to join its team to work on AI4Code, LLM, and natural language processing. This group is entrusted with developing core algorithms/capabilities for Amazon Q Developer. At NGDE's science team you will invent, implement, and deploy state of the art AI algorithms and systems for developers. You will build prototypes and explore conceptually new large scale AI solutions. 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.About the teamAWS 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.Diverse 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.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 ...

As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazon’s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers’ businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon’s real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use.AWS Industry Products (IP) is a new AWS engineering organization chartered to build new AWS products by applying Amazon’s innovation mechanisms along with AWS digital technologies to transform the world, industry by industry. We dive deep with leaders and innovators to solve the problems which block their industries, enabling them to capitalize on new digital business models. Simply put, our goal is to use the skill and scale of AWS to make the benefits of a connected world achievable for all businesses. We are looking for Research Scientists who are passionate about transforming industries through AI. This is a unique opportunity to not only listen to industry customers but also to develop AI and generative AI expertise in multiple core industries. You will join a team of scientists, product managers and software engineers that builds AI solutions in automotive, manufacturing, healthcare, sustainability/clean energy, and supply chain/operations domains. Leveraging and advancing generative AI technology will be a big part of your charter as we seek to apply the latest advancements in generative AI to industry-specific problemsUsing your in-depth expertise in machine learning and generative AI, you will take the lead on tactical and strategic initiatives to deliver reusable science components and services that differentiate our industry products and solve customer problems. You will be the voice of scientific rigor, delivery, and innovation as you work with our segment teams on AI-driven product differentiators. You will conduct and advance research in AI and generative AI within and outside Amazon.Extensive knowledge of both state-of-the-art and emerging AI methods and technologies is expected. Hands-on knowledge of generative AI, foundation models and commitment to learn and grow in this field are expected. Basic qualificationsPhD, or Master's degree and 10+ years of quantitative field research experienceExperience investigating the feasibility of applying scientific principles and concepts to business problems and productsExperience analyzing both experimental and observational data setsPreferred qualificationsKnowledge of R, MATLAB, Python or similar scripting languageAbout the teamWhy 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.Diverse 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.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.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. BASIC QUALIFICATIONS- 10+ years of tech industry or equivalent experience- PhD in a quantitative discipline such as statistics, mathematics, economics, computer science, or any related quantitative field- Experience working effectively with science, data processing, and software engineering teams ...

The Fulfillment by Amazon (FBA) and Supply Chain by Amazon (SCA) empower third-party sellers world-wide to use Amazon's cutting-edge logistics, warehousing, distribution, fulfillment, and transportation services. These services ensure products remain in stock, customer orders are fulfilled fast and reliably, while end-to-end supply chain costs are reduced. As a result, sellers can focus less on supply chain management and more on developing outstanding products, delighting customers, and scaling their businesses. The FBA team is looking for a passionate, curious, and creative Research Scientist with expertise in operations research, machine learning or statistics, preferably with a focus on pricing and market design, and a proven record of solving business problems through scalable modeling and analytical skills. As a research scientist in the team, you will be responsible for designing and implementing cutting edge optimization and ML models, building automated inventory, logistics, capacity and revenue management systems while collaborating with business and software teams to solve key challenges facing the worldwide FBA business. Such challenges include 1) designing end-to-end supply and demand management systems, 2) developing and improving optimization and ML models to support FBA sellers in growing their businesses, 3) creating decision-support tools that minimize the cognitive burden on sellers in navigating supply chain and operational complexities, 4) ensuring worldwide Amazon customers have access to the broadest selection of products from FBA sellers, and 5) driving cost efficiencies across end-to-end FBA supply chain. Unlike many companies that purchase off-the-shelf planning systems, we design and build custom solutions to suit Amazon's unique needs. Our team members are at the forefront of supply chain innovation, tackling some of the industry's most challenging problems alongside top product managers, research scientists, statisticians, economists, and software developers. We value individuals who exhibit deep technical proficiency, a desire for learning new areas, and a track record of delivering tangible results while fostering personal growth, team development, and career advancement.A day in the lifeAs a scientist on the team, you will be involved with every aspect of the process—from idea generation, business analysis and scientific research to development and deployment of advanced models—granting you a profound sense of ownership. Your solutions have the potential to drive billions of dollars in impact for Amazon's third-party seller business. From day one, you will collaborate with experienced scientists, engineers, and product managers who are passionate about their work. Additionally, you will engage with Amazon's broader decision and research science community, enriching your perspective and mentoring fellow engineers and scientists. The ideal candidate will have the strong expertise in applying operations research methodologies to solve a wide variety of supply chain problems, involving millions of unique products, hundreds of thousands of Selling Partners, and tens of millions of customers worldwide. You will strive for simplicity and demonstrate judgment backed by mathematical rigor, as you continually seek opportunities to innovate, build, and deliver. An entrepreneurial spirit, adaptability to diverse roles, and agility in a fast-paced, high-energy, highly collaborative environment are essential.About the teamSellers are a crucial part of Amazon's ecosystem, playing an integral role in our mission to offer the Earth's largest selection and lowest prices. FBA is a service that enables third-party sellers to outsource order fulfillment to Amazon, and leverage Amazon’s world-class facilities to provide customers Prime delivery promise. By partnering with Amazon, sellers benefit from powerful, cost-effective solutions that leverage our scale and technology, gain access to Prime members worldwide, boost their sales, and free up time to focus on inventing amazing products for customers. To further ease supply chain and operational complexities for our selling partners, Amazon introduced Supply Chain by Amazon (SCA), an end-to-end, fully automated suite of supply chain services. With SCA, Amazon handles everything from picking up inventory from global manufacturing facilities, shipping across borders, managing customs clearance and ground transportation, to storing inventory in bulk, managing replenishment across Amazon and other sales channels, and delivering directly to customers— all without sellers having to worry about managing their supply chain. A pivotal service within SCA is Amazon Warehousing and Distribution, which offers best-in-class bulk storage and distribution services, ensuring sellers remain well-stocked across all their sales and fulfillment channels while reducing overall supply chain costs. The FBA team is at the heart of this operation, responsible for inventory management, automated replenishment, fulfillment, pricing, resource planning, capacity management, and a wide range of operational recommendation services for sellers. We focus on understanding seller behavior and experience, building automated tools and assistants, recommending optimal actions, designing seller policies and incentives, and developing science-driven products and services that empower third-party sellers to grow their businesses. We develop and innovate science-driven solutions at the intersection of machine learning, statistics, economics, operations research, and data analytics. Our work spans the full stack, from foundational backend systems to cutting-edge user interfaces. Our culture is rooted in rapid prototyping, rigorous experimentation, and data-driven decision-making.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of quantitative field research experience- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products- Ph.D. in Operations Research, Machine Learning, Statistics, Computer Science, Applied Mathematics, Operations Management, Industrial Engineering, Economics or a related field.- 2+ years of experience in solving complex problems in the area of operations research, statistics or machine learning, as well as in developing strategies for large-scale supply chain, transportation and logistics networks.- Ability to perform quantitative, economic, and numerical analyses of large-scale systems under uncertainty using statistical and optimization tools such as Python, R and XPRESS to determine solution strategies for complex decision-making problems.- Fluency in using mathematical optimization or machine learning to develop solution methods to be used by in-house decision support tools and software.- Proficiency working with Python, SQL and/or C/C++.- Excellent written and verbal communication skills while addressing both technical and business people, ability to speak at a level appropriate for the audience, and skills to present business cases, and document models, analyses, and results to influence important decisions. ...

Does the idea of creating technology solutions for delivering 11 Billion+ packages across the globe excite you? If yes, come join a fun-loving, diverse, and creative team at Amazon Last Mile! The vision of the team is "To create Earth’s safest, most adaptive, and efficient plans for Last Mile logistics". The Last Mile Delivery Technology team is instrumental in impacting customer satisfaction directly, by devising innovative ways to deliver packages quickly and cost-effectively to the customers, and at scale using Artificial Intelligence (AI), Machine Learning and Operations Research solutions. Last Mile Delivery Technology organization supports the design, planning and execution of last mile transportation for Amazon’s various parcel and grocery delivery programs. All these programs require a large number of decision support systems to operate at scale and serve our customers, spanning demand planning, jurisdiction planning, delivery channel and network design, capacity planning for on the road and under the roof at delivery stations, routing inputs and route optimization. While these decision support systems have thus far been approached through the lens of traditional optimization and machine learning, we are looking to re-envision this space and pursue Foundational AI research, to innovate and advance the state of these decision support systems. Specifically, we are looking to develop foundational models (including Large Language Models, Multimodal Language Models, Multimodal Models), and adaptations to serve last mile use cases. Beyond Amazon the work developed will spur new fundamental knowledge and innovation in the logistics space. We are looking for candidates with knowledge and experience in designing and developing state-of-art AI solutions (including development and application of advanced deep learning algorithms, foundational models, multimodal generative AI solutions, reinforcement learning), to join our team. Demonstrated experience scaling and optimizing the training and inference of these models, building real world solutions, to meet the customer use cases is preferred. Proven track record of publishing in major AI conferences and demonstrated experience working in industry will be preferred.Job Location : Bellevue WA or Austin TX.Key job responsibilitiesCandidates will be responsible for developing Foundational AI solutions, to serve the myriad of decision support use cases across last mile. In this role, you will be expected to define new research avenues, explore, adopt, and invent new machine learning techniques, implement scalable science and engineering solutions, contribute software to production systems, conduct rigorous experiments, publish results, influence technical and business leadership and ensuring that research is translated into practice. You will be working with a team of scientists and engineers, helping shape the strategic and tactical vision, and contribute hands on to foundational research efforts in last mile. A day in the lifeSitting at the core of Amazon’s Last Mile business, Routing and Planning (RaP) invents technology solutions that deliver toward the RaP vision: to create earth’s safest, most adaptive, and efficient plans for Last Mile logistics. RaP serves a diverse set of external and internal customers. For Amazon End Customers and transporters, we build solutions to deliver 11B packages and services to arrive at the right place and time, while meeting the growing preference for speed and precision. For internal customers, we build and delivery routing solutions Worldwide adding up to a $1B USD, across multiple amazon businesses ranging from Amazon Logistics, Amazon X-tra Large to Same/Sub-Same Day Deliveries, Fresh and Groceries etc using multiple mode of transports. If the opportunity to innovate, create and deliver first-time solutions alongside world-class engineers and scientists e.g. building a new delivery foundational model from scratch utilizing data at an unprecedented scale in the industry excites you, this is the place for you. About the teamThe Last Mile (LM) Science organization serves two primary functions: (1) maintaining and enhancing the components which provide the essential intelligence in nearly every LM system, and (2) creating the science which will enable the continued growth of Amazon in the future. The systems used on a daily basis by the Last Mile to deliver packages from the station to the customer’s doorstep contains embedded models developed by the science team, or relies on inputs derived from these models. These models determine how efficiently Amazon can serve its customers and at what cost.BASIC QUALIFICATIONS- 5+ years of building machine learning models or developing algorithms for business application experience- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 10+ years of industry or academic research experience- Knowledge of programming languages such as C/C++, Python, Java or Perl- Experience with neural deep learning methods and machine learning ...

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!As an Applied Science Manager in Machine Learning, you will: - Directly manage and lead a cross-functional team of Applied Scientists, Data Scientists, Economists, and Business Intelligence Engineers.- Develop and manage a research agenda that balances short term deliverables with measurable business impact as well as long term investments.- Lead marketplace design and development based on economic theory and data analysis.- Provide technical and scientific guidance to team members.- Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment- Advance the team's engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner.- Develop science and engineering roadmaps, run annual planning, and foster cross-team collaboration to execute complex projects.- Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management.- Collaborate with business and software teams across Amazon Ads.- Stay up to date with recent scientific publications relevant to the team.- Hire and develop top talent, provide technical and career development guidance to scientists and engineers within and across the organization.Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.Team video ~ https://youtu.be/zD_6Lzw8raE BASIC QUALIFICATIONS- 4+ years of applied research experience- 3+ years of scientists or machine learning engineers management experience- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Knowledge of ML, NLP, Information Retrieval and Analytics- Experience programming in Java, C++, Python or related language ...

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. As a Applied Scientist at the intersection of machine learning and the life sciences, you will participate in developing exciting products for customers. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with others teams.BASIC QUALIFICATIONS- PhD in computer science, machine learning, engineering, or related fields- Experience with programming languages such as Python, Java, C++- Expert knowledge of machine learning and deep learning; solid understanding of large language models. ...

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 ...

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 ...

Are you excited by the idea of developing personalized experiences for Amazon customers as they shop? Are you looking for new challenges and to solve hard science problems while applying state-of-the-art recommendation system modeling techniques? Join us and you'll help millions of customers make informed purchase decisions while also advancing the state of Amazon's science by publishing research!Key job responsibilities- Participate in the design, development, evaluation, deployment and updating of data-driven models for shopping personalization.- Use expertise in supervised and uplift learning algorithms to improve ML performance- Research and implement novel ML and statistical approaches to add value to the business.- Design A/B tests and conduct statistical analysis on their results- Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers- Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area- Present and publish science research, contributing to Amazon's science community- Mentor junior engineers and scientists.About the teamOur team's mission is to surface the right payments-related recommendations to customers at the right time, helping create a rewarding and successful shopping experience for Amazon's customers. Our team's culture is highly collaborative, with an emphasis on supporting each other and learning from one another. We dedicate time each week to focus on personal development and expanding our knowledge as a team. We also highly value having a big impact, both for Amazon's business and for our customers.BASIC QUALIFICATIONS- 4+ years of applied research experience- 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- Experience with reinforcement learning- Publication record on machine learning methods ...

Alexa International Tech (AIT) team is looking for a passionate, talented, and inventive Senior Applied Scientist to help build industry-leading technology with Large Language Models (LLM's) and multimodal systems, requiring strong deep learning and generative models knowledge. Key job responsibilitiesAs a Senior Applied Scientist with the AIT team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs. Your work will directly impact our international customers in the form of products and services that make use of digital assistance technology. You will leverage Amazon’s heterogeneous data sources, unique but diverse international customer nuances and large-scale computing resources to accelerate advances in voice domain in multi-modal setup. The ideal candidate possesses a solid understanding of machine learning fundamentals and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environments to tackle complex challenges, and excel at swiftly delivering impactful solutions while iterating based on user feedback. A day in the life- Analyze, understand, and model customer behavior and the customer experience based on large scale data - especially showing passion towards solving for international customer-centric challenges- Build novel online & offline evaluation metrics and methodologies for personal digital assistants and customer scenarios on multi-modal devices- Innovate and deliver deep learning-based innovation across life-cycle such as policy-based learning, international customer specific model performance tuning- Quickly experiment and setup experimentation framework for agile model and data analysis or A/B testing- Contribute through industry first research to drive the innovation forwardBASIC 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 ...

Are you excited about developing AI/ML solutions to revolutionize robotics and automation? Are you looking for opportunities to build and deploy them on real problems at truly vast scale? At Amazon Fulfillment Technologies and Robotics we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class customer experience - at Amazon scale. The Research team at Amazon Robotics is seeking a passionate hands-on Applied Scientist to innovate in the field of planning for fleets of mobile robots. The focus of this position is optimizing movement in warehouses that feature thousands of robots in constant motion moving inventory around the building. Relevant research topics include planning and scheduling for multi robot systems, multi-agent path finding, and developing ML models to render fleet behavior adaptable to varying operating conditions. The work includes eliciting and addressing basic research questions from AR's rich application settings, running large-scale A/B tests on robots in our facilities, and collaborating with engineering teams to deploy solutions in our vast robot fleet.Key job responsibilities* Research vision - Where should we be focusing our efforts* Research delivery - Proving/dis-proving strategies in offline data or in simulation* Production studies - Insights from production data or ad-hoc experimentation* Production implementation - Building key parts of deployed algorithms or modelsA 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 teamYou would join our Movement Science team that includes scientists with backgrounds in planning and scheduling, machine learning, and robotics. We develop novel planning algorithms and machine learning methods and apply them to real-word robotic warehouses, including: - Planning and coordinating the paths of thousands of robots - Dynamic allocation and scheduling of tasks to thousands of robots - ML models that adapt system behavior to varying operating conditions - Co-design of layouts and the algorithms to optimize movement on themOur team is part the Research, Applied, and Data Science organization within Amazon Robotics, a hub to foster innovation and support scientists across Amazon Robotics.BASIC 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 patents or publications at top-tier peer-reviewed conferences or journals- Experience with any of the following (preferably in the context of multi-robot/multi-agent systems): automated planning, scheduling, heuristic search, deep learning, transformer-based models, foundation models, robotics ...

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 ...

Amazon Robotics is seeking a Principal Applied Scientist to develop state-of-the-art algorithms to control the fleet of 750,000 mobile robots in Amazon’s order fulfillment network. You will have the chance to solve complex planning and coordination problems and see your solutions come to life in Amazon’s warehouses!In this position, you will own the science of planning and scheduling fleet activities to achieve system-level objectives across a broad range of building types and workflows. You will improve the algorithms that control today’s global robotic fleet to unlock new opportunities for Amazon’s evolving network, as well as develop new capabilities from the ground up. You will explore how to leverage the power of our robotic mobility foundation model to predict the motion of the fleet to enable new ways of making decisions at scale. You will influence the design of future warehouses and the integration of new robotic technologies.This role offers the chance to have broad impact on the next wave of robotics You will collaborate with brilliant colleagues in a culture that values ingenuity, teamwork and delivering impact. Come join our mission to pioneer the future of automation!About the teamOur multi-disciplinary science team includes scientists with backgrounds in simulation, planning and scheduling, grasping and manipulation, machine learning, and operations research. We develop novel planning algorithms and machine learning methods and apply them to real-word robotic warehouses, including:* Planning and coordinating the paths of thousands of robots* Dynamic allocation and scheduling of tasks to thousands of robots* Learning how to adapt system behavior to varying operating conditions* Co-design of robotic logistics processes and the algorithms to optimize themOur team also serves as a hub to foster innovation and support scientists across Amazon Robotics. We also coordinate research engagements with academia, such as the Robotics section of the Amazon Research Awards.BASIC QUALIFICATIONS* PhD degree in Robotics, CS or related technical field* 10+ years of relevant, broad research experience after a PhD degree* Experience programming in C++, Java, Python or related language* Experience using state of the art planning and machine learning methods* Strong publication record with contributions to leading conferences/journals ...

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. 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 organization'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. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!Our team, Off-Search Sourcing and Relevance, has a mission to deliver relevant and useful shopping experience at non-Search pages at Amazon.com. We innovate technology solutions, develop machine learning models that incorporate deep product and shopper understanding, and conduct A/B tests to ensure that we identify all useful and relevant advertisements and provide them to downstream systems for click through prediction and ad auction.We are looking for a passionate Applied Scientist who has technical expertise in information retrieval, Natural Language Processing (NLP), and Large Language Models (LLM). In addition to having hands-on experience in building ML-based solutions, an ideal candidate should be able to create and articulate a customer-centric science vision, show willingness to continuously learn about new scientific approaches, and enjoy operating in startup-like environment. Key job responsibilities* Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities* Develop scalable and effective machine-learning models and optimization strategies to solve business problems* Run regular A/B experiments, gather data, and perform statistical analysis* Work closely with software engineers to deliver end-to-end solutions into production* Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving* Conduct research on new machine-learning modeling to optimize all aspects of Sponsored Products businessBASIC 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 ...

Shape the Future of Human-Machine InteractionAre you a master of natural language processing, eager to push the boundaries of conversational AI? Amazon is seeking exceptional graduate students to join our cutting-edge research team, where they will have the opportunity to explore and push the boundaries of natural language processing (NLP), natural language understanding (NLU), and speech recognition technologies. Imagine waking up each morning, fueled by the excitement of tackling complex research problems that have the potential to reshape the world. You'll dive into production-scale data, exploring innovative approaches to natural language understanding, large language models, reinforcement learning with human feedback, conversational AI, and multimodal learning. Your days will be filled with brainstorming sessions, coding sprints, and lively discussions with brilliant minds from diverse backgrounds.Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated..Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology.Amazon has positions available for Natural Language Processing & Speech Applied Science Internships in, but not limited to, Bellevue, WA; Boston, MA; Cambridge, MA; New York, NY; Santa Clara, CA; Seattle, WA; Sunnyvale, CA. Key job responsibilitiesWe are particularly interested in candidates with expertise in: NLP/NLU, LLMs, Reinforcement Learning, Human Feedback/HITL, Deep Learning, Speech Recognition, Conversational AI, Natural Language Modeling, Multimodal Learning.In this role, you will work alongside global experts to develop and implement novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of Natural Language Processing and Speech Technologies. You will tackle challenging, groundbreaking research problems on production-scale data, with a focus on natural language processing, speech recognition, text-to-speech (TTS), text recognition, question answering, NLP models (e.g., LSTM, transformer-based models), signal processing, information extraction, conversational modeling, audio processing, speaker detection, large language models, multilingual modeling, and more.The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment.A day in the life- Develop novel, scalable algorithms and modeling techniques that advance the state-of-the-art in natural language processing, speech recognition, text-to-speech, question answering, and conversational modeling.- Tackle groundbreaking research problems on production-scale data, leveraging techniques such as LSTM, transformer-based models, signal processing, information extraction, audio processing, speaker detection, large language models, and multilingual modeling.- Collaborate with cross-functional teams to solve complex business problems, leveraging your expertise in NLP/NLU, LLMs, reinforcement learning, human feedback/HITL, deep learning, speech recognition, conversational AI, natural language modeling, and multimodal learning.- Thrive in a fast-paced, ever-changing environment, embracing ambiguity and demonstrating strong attention to detail.BASIC QUALIFICATIONS- Are enrolled in a PhD- Are 18 years of age or older- Work 40 hours/week minimum and commit to 12 week internship maximum- Can relocate to where the internship is based- Experience programming in Java, C++, Python or related language- Experience with one or more of the following: Natural Language Processing/Understanding, Large Language Models, Reinforcement Learning, Human Feedback/HITL, Deep Learning, Speech Recognition, Conversational AI, Natural Language Modeling, Multimodal Learning ...

Amazon Search is looking for an Applied Scientist to build the next-generation Autocomplete and Spelling Correction experience. Autocomplete provides real-time suggestions as customers type in the search box. It serves as a virtual assistant on customer’s shopping journey. Our suggestions complete customers’ thoughts and help them to explore Amazon’s vast product offering. Spelling correction recovers the spelling errors in the queries, allowing customers to search effortlessly in any language they prefer, without worrying about making spelling mistakes. You will have the opportunities to leverage the latest developments in Natural Language Processing, Deep Learning, and Reinforcement Learning to re-invent customers’ shopping experience. Your work will touch the life of hundreds of millions customers and deliver billion-dollar business impact.You will love the job if you enjoy brining the cutting-edge research to people’s (and yours) day-to-day life. It’s a great feeling to realize the model you deployed yesterday has helped your shopping journey today. You will work closely with scientists and engineers to do fast-pace model development and experiment iterations. You will have access to Amazon’s rich datasets, AWS’s massive computation power, and science and engineering leaders across the company.As an applied scientist, you willDrive the science vision and roadmap.Develop data-driven solutions for the real-world, large scale problems.Deliver and maintain software and models in the production environment.Lead cross-functional collaborations between product, design, and engineering.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 ...

As part of Alexa CAS team, our mission is to provide scalable and reliable evaluation of the state-of-the-art Conversational AI. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP), to invent and build end-to-end evaluation of how customers perceive state-of-the-art context-aware conversational AI assistants.A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also have hands-on experiences in building Generative AI solutions with LLMs, including Supervised Fine-Tuning (SFT), In-Context Learning (ICL), Learning from Human Feedback (LHF), etc.As an Applied Scientist, you will leverage your technical expertise and experience to collaborate with other talented applied scientists and engineers to research and develop novel methods for evaluating conversational assistants. You will analyze and understand user experiences by leveraging Amazon’s heterogeneous data sources and build evaluation models using machine learning methods.Key job responsibilities- Design, build, test and release predictive ML models using LLMs- Ensure data quality throughout all stages of acquisition and processing, including such areas as data sourcing/collection, ground truth generation, normalization, and transformation.- Collaborate with colleagues from science, engineering and business backgrounds.- Present proposals and results to partner teams in a clear manner backed by data and coupled with actionable conclusions- Work with engineers to develop efficient data querying and inference infrastructure for both offline and online use casesAbout the teamCentral Analytics and Research Science (CARS) is an analytics, software, and science team within Amazon's Conversational Assistant Services (CAS) organization. Our mission is to provide an end-to-end understanding of how customers perceive the assistants they interact with – from the metrics themselves to software applications to deep dive on those metrics – allowing assistant developers to improve their services. Learn more about Amazon’s approach to customer-obsessed science on the Amazon Science website, which features the latest news and research from scientists across the company. For the latest updates, subscribe to the monthly newsletter, and follow the @AmazonScience handle and #AmazonScience hashtag on LinkedIn, Twitter, Facebook, Instagram, and YouTube.BASIC QUALIFICATIONS- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience- Experience building machine learning models or developing algorithms for business application- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience with programming languages such as Python, Java, C++- Hands-on experience and deep understanding of the Large Language Models architectures ...

AWS AI is looking for passionate, talented, and inventive Applied Scientists with a strong machine learning background to help build industry-leading Conversational AI Systems. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Understanding (NLU), Dialog Systems including Generative AI with Large Language Models (LLMs) and Applied Machine Learning (ML).As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services that make use language technology. You will gain hands on experience with Amazon’s heterogeneous text, structured data sources, and large-scale computing resources to accelerate advances in language understanding.We are hiring in all areas of human language technology: NLU, Dialog Management, Conversational AI, LLMs and Generative AI.A day in the lifeThe team uses generative AI and foundation models to reimagine the experience of all customers on AWS. We explore new technologies and find creative solutions. Curiosity and an explorative mindset can find a place here to impact the life of engineers around the world.If you are excited about this space and want to enlighten your peers with new capabilities, this is the team for you.We are open to hiring candidates to work out of one of the following locations:Santa Clara, CA, USAAbout the teamAWS 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.Diverse 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- 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 ...

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 invent and apply the most advanced machine learning and NLP techniques to create the best customer engagement experience on the earth? Do you want to revolutionize the way how customers solve their issues and get their questions answered? At Customer Engagement Technology (CET), we develop peculiar products that help customers solve problems. We innovate on behalf of customers, developing Bot, self-service, and associate-facing products that delight customers and support our world class customer service workforce. We are looking for talented Postdoctoral Scientists to join our CET Machine Learning team in Seattle, WA for a one-year, full-time research position to work on research and development of task oriented dialogue agents for the customer support domain. We utilize Large Language Models (LLMs) to address challenges within TOD systems, such as Natural Language Generation for generating system responses based, state tracking, decision making etc. We publish our research in top tier NLP and AI venues (EMNLP, ACL, AAAI, etc), and deploy ML powered chatbots primarily in the customer returns domain. 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.BASIC QUALIFICATIONS• PhD in a relevant field, received within 2 years of starting the program • Proven publication record in Machine Learning, Computer Vision, AI, Computer Science, or other related technical fields • Experience in data science and quantitative research • Proficiency in technologies relevant to the subfield• Experience in Natural Language Processing, and in particular Large Language Models ...