Feedback
Follow Us
August 14 - 18, 2021
Singapore
Conference
KDD 2021

Overview

The Knowledge Discovery and Data Mining Conference brings together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data.

Sponsorship Details

Gold
Conference website
Related content
Connect with us

Amazon organizing committee members

Accepted publications

Workshop keynotes

  • Heng Ji
    Heng Ji
    Amazon Scholar
    Document Intelligence Workshop
  • Li Lihong
    Lihong Li
    MARBLE Workshop
    A Map of Bandits for E-commerce
  • Yu-Liu.jpg
    Yi Liu
    MARBLE Workshop
    A Map of Bandits for E-commerce
  • Anoop-Deoras.jpeg
    Anoop Deoras
    2nd International Workshop on Industrial Recommendation Systems
  • Shen-Wang.jpg
    Shen Wang
    Graph Neural Networks on Anomaly Detection

Workshops

KDD 2021 TrueFact Workshop on Making a Credible Web for Tomorrow
August 15
Website: https://www.microsoft.com/en-us/research/event/kdd-2021-truefact-workshop-making-a-credible-web-for-tomorrow/
Solving price per unit problem around the world: Formulating fact extraction as question answering
Tarik Arici, Kushal Kumar, Hayreddin Ceker, Anoop S V K K Saladi, Ismail Tutar
2021
Machine learning
KDD 2021 WIT Workshop on Deriving Insights from User-Generated Text
August 15
Amazon organizer: Luna Dong

Website: https://megagon.ai/wit
KDD 2021 Workshop on Multi-Armed Bandits and Reinforcement Learning (MARBLE)
August 15
Amazon organizer: Chu Wang

Website: https://sites.google.com/view/marble-kdd
A map of bandits for e-commerce
Yi Liu, Lihong Li
2021
Search and information retrieval
Markov decision process modeled with bandits for sequential decision making in linear-flow
Wenjun Zeng, Yi Liu
2021
Machine learning
KDD 2021 International Workshop on Industrial Recommendation Systems
August 15
Amazon organizers: George Karypis, Anoop Deoras, Athanasios N. Nikolakopoulos, Mansi Mane,

Website: https://irsworkshop.github.io/2021/
Personalized compatibility metric learning
Meet Taraviya, Anurag Beniwal, Yen-Liang Lin, Larry Davis
2021
Search and information retrieval
Two-stage voice application recommender system for unhandled utterances in intelligent personal assistant
Wei Xiao, Qian Hu, Thahir Mohamed, Zheng Gao, Xibin Gao, Radhika Arava, Mohamed AbdelHady
2021
Conversational AI
KDD 2021 Workshop on Anomaly and Novelty Detection, Explanation and Accommodation (ANDEA)
August 15
Amazon organizer: Anton van den Hengel

Website: https://sites.google.com/view/andea2021
KDD 2021 Workshop on Data-Efficient Machine Learning
August 15
Amazon organizers: Sumeet Katariya, Nikhil Rao, Chandan Reddy

Website: https://demalworkshop.github.io/kdd2021/index.html
Active two-phase learning for classification of large datasets with extreme class-skew
Tarun Gupta, Sedat Gokalp
2021
Machine learning
Establishing reliability in crowdsourced voice feedback (CVF) and evaluating the reliability in the absence of ground-truth
Aashish Jain, Sudeeksha Murari
2021
Conversational AI
RoBERTaIQ: An efficient framework for automatic interaction quality estimation of dialogue systems
Saurabh Gupta, Xing Fan, Derek Liu, Benjamin Yao, Yuan Ling, Kun Zhou, Tuan-Hung Pham, Chenlei (Edward) Guo
2021
Conversational AI
Towards NLU model robustness to ASR errors at scale
Yaroslav Nechaev, Weitong Ruan, Imre Kiss
2021
Conversational AI
Improving natural language understanding accuracy by pre-adapting to live traffic
Lisheng Fu, Konstantine Arkoudas
2021
Conversational AI
Search based self-learning query rewrite system in conversational AI
Xing Fan, Eunah Cho, Xiaojiang Huang, Chenlei (Edward) Guo
2021
Conversational AI
KDD 2021 Workshop on Pretraining: Algorithms, Architectures, and Applications
August 15
Website: https://www.aminer.cn/pretrain_kdd2021
Graphire: Novel Intent Discovery with Pretraining on Prior Knowledge using Contrastive Learning
Xibin Gao, Radhika Arava, Qian Hu, Thahir Mohamed, Wei Xiao, Zheng Gao, Mohamed AbdelHady
2021
Conversational AI
Enhancement and analysis of TARS few-shot learning model for product attribute extraction from unstructured texts
Pascual Martinez-Gomez, Giorgos Papachristoudis, Jon Blauvelt, Eric Rachlin, Saul Simhon
2021
Conversational AI
KDD 2021 Workshop on Document Intelligence Workshop
August 15
Keynote Speaker: Heng Ji

Website: https://document-intelligence.github.io/DI-2021/
KDD 2021 Workshop on Fragile Earth
August 14 - August 15
Website: https://ai4good.org/fragile-earth-2021/
Position paper: Reducing Amazon’s packaging waste using multimodal deep learning
Prasanth Meiyappan, Matthew Bales
2021
Related: How deep learning is reducing Amazon’s packaging waste
Computer vision

Tutorials

KDD 2021 Tutorial on Explainability for Natural Language Processing
August 13
Amazon organizer: Kun Qian

Website: https://xainlp.github.io/kddtutorial/
KDD 2021 Tutorial on Deep Learning on Graphs for Natural Language Processing
August 13
Amazon organizer: Heng Ji

Website: https://dlg4nlp.github.io/
KDD 2021 Tutorial on All You Need to Know to Build a Product Knowledge Graph
August 14
Amazon organizers: Nasser Zalmout, Xin Luna Dong, Xian Li, Chenwei Zhang, Yan Liang

Website: https://naixlee.github.io/Product_Knowledge_Graph_Tutorial_KDD2021/

Related content

Work with us

See more jobs See more jobs
2024 Applied Scientist Intern
IL, Tel Aviv
This role is available across multiple locations in Tel-Aviv and Haifa. Amazon Internships have start dates throughout the year and can vary in length from 3-6 months for full-time. Please note these are not remote internships. Are you a MS or PhD student interested in a 2024 Internship in the field of Applied Sciences? Are you interested in machine learning, deep learning, automated reasoning, speech, robotics, computer vision, optimization, or quantum computing? If so, we want to hear from you! We are looking for scientists with interest in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. For more information on the Amazon Science community please visit the Science hub page: https://www.amazon.science/ For more information on the Amazon Science EMEA internship program or to join us for one of our upcoming informational webinars please visit this page: https://amazonscienceopportunitiesemea.splashthat.com/ Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create technical roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. We are open to hiring candidates to work out of one of the following locations: Haifa, ISR | Tel Aviv, ISR
Applied Scientist, EU GTS RAS, GTS RAS
GB, London
Have you ever wished to build high standard Operations Research and Machine Learning algorithms to optimize one of the most complex logistics network? Have you ever ordered a product on Amazon websites and wondered how it got delivered to you so fast, and what kinds of algorithms & processes are running behind the scenes to power the whole operation? If so, this role is for you. The team: Global transportation services, Research and applied science - Operations is at the heart of the Amazon customer experience. Each action we undertake is on behalf of our customers, as surpassing their expectations is our passion. We improve customer experience through continuously optimizing the complex movements of goods from vendors to customers throughout Europe. - Global transportation analytical teams are transversal centers of expertise, composed of engineers, analysts, scientists, technical program managers and developers. We are focused on Amazon most complex problems, processes and decisions. We work with fulfillment centers, transportation, software developers, finance and retail teams across the world, to improve our logistic infrastructure and algorithms. - GTS RAS is one of those Global transportation scientific team. We are obsessed by delivering state of the art OR and ML tools to support the rethinking of our advanced end-to-end supply chain. Our overall mission is simple: we want to implement the best logistics network, so Amazon can be the place where our customers can be delivered the next-day. The role: Applied scientist, speed and long term network design The person in this role will have end-to-end ownership on augmenting RAS Operation Research and Machine Learning modeling tools. They will help understand where are the constraints in our transportation network, and how we can remove them to make faster deliveries at a lower cost. Concretely, you will be responsible for designing and implementing state-of-the-art algorithmic in transportation planning and network design, to expand the scope of our Operations Research and Machine Learning tools, to reflect the constantly evolving constraints in our network. You will enable the creation of a product that drives ever-greater automation, scalability and optimization of every aspect of transportation, planning the best network and modeling the constraints that prevent us from offering more speed to our customer, to maximize the utilization of the associated resources. The impact of your work will be in the Amazon EU global network. The product you will build will span across multiple organizations that play a role in Amazon’s operations and transportation and the shopping experience we deliver to customer. Those stakeholders include fulfilment operations and transportation teams; scientists and developers, and product managers. You will understand those teams constraints, to include them in your product; you will discuss with technical teams across the organization to understand the existing tools and assess the opportunity to integrate them in your product. You will also be challenged to think several steps ahead so that the solutions you are building today will scale well with future growth and objective (e.g.: sustainability). You will engage with fellow scientists across the globe, to discuss the solutions they have implemented and share your peculiar expertise with them. This is a critical role and will require an aptitude for independent initiative and the ability to drive innovation in transportation planning and network design. Successful candidates should be able to design and implement high quality algorithm solutions, using state-of-the art Operations Research and Machine Learning techniques. You will have the opportunity to thrive in a highly collaborative, creative, analytical, and fast-paced environment oriented around building the world’s most flexible and effective transportation planning and network design management technology. Key job responsibilities - Engage with stakeholders to understand what prevents them to build a better transportation network for Amazon - Review literature to identify similar problems, or new solving techniques - Build the mathematical model representing your problem - Implement light version of the model, to gather early feed-back from your stakeholders and fellow scientists - Implement the final product, leveraging the highest development standards - Share your work in internal and external conferences - Train on the newest techniques available in your field, to ensure the team stays at the highest bar About the team GTS Research and Applied Science is a team of 15 scientists and engineers whom mission is to build the best decision support tools for strategic decisions. We model and optimize Amazon end-to-end operations. The team is composed of enthusiastic members, that love to discuss any scientific problem, foster new ideas and think out of the box. We are eager to support each others and share our unique knowledge to our colleagues. We are open to hiring candidates to work out of one of the following locations: London, GBR
Economist, Global Media and Entertainment (GME) Econ
US, WA, Seattle
Amazon’s Global Media and Entertainment (GME) organization is creating the future of entertainment where creative content, innovation, and commerce come together. We leverage Amazon’s unique expertise across video, music, gaming, and more to create a truly immersive entertainment experience. Our team, GME Economics, is focused on building strategic science tools to optimize Amazon’s entertainment offerings, so that we can provide a great customer experience while operating as a sustainable and profitable business. This role will build and expand long-term measurement models serving all GME businesses, making strong causal inference skills essential. The GME business context is complex, ambiguous, and can change quickly. You'll need to be adaptable and resourceful, converting complex business problems into estimable econometric problems, and building solutions that anticipate future business needs. Once the model is built, you'll partner hands-on with engineers to productionize it, ensuring the output is high quality and that computation is efficient. Our team values excellent written and verbal communication with partners of all levels, with technical and nontechnical backgrounds. You'll need to translate data and findings into actionable insights for leaders with the same skill that you explain the nuances of your identification assumptions to scientists, or describe the logical flow of your estimations to engineers. Our healthy team culture is supportive and fast-paced, and we prioritize learning, growth, and helping each other to continuously raise the bar. We think big, taking on high-risk, high-reward projects based on novel scientific approaches. As a central science team, we work hard to build trust with partners, who always have fresh problems for us to tackle. Impact and Career Growth: In today’s entertainment landscape, critical decisions are made with data and economic models. You’ll help leaders ask the right questions, and then deliver data-driven answers, creating the future of GME at Amazon. You’ll help define a long-term science vision and translate it into an actionable roadmap. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding – a perfect recipe for career growth as an economist in tech. Key job responsibilities • Design and build econometric models, especially causal models, to measure the value of the business and its many features • Develop science products from concept to prototype to production, incorporating feedback from scientists and business partners • Independently identify and pursue new opportunities to leverage economic insights across GME businesses • Collaborate with PMs to build product roadmaps, ensuring our work meets the needs of our stakeholders and then communicating progress and findings to them • Write business and technical documents communicating business context, methods, and results to business leadership and other scientists • Work with engineers within and outside our org to productionize science models • Serve as a technical reviewer for our team and related teams, including document and code reviews We are open to hiring candidates to work out of one of the following locations: Los Angeles, CA, USA | New York, NY, USA | Seattle, WA, USA
Research Scientist - Ergonomics
US, WA, Seattle
We are designing the future. If you are in quest of an iterative fast-paced environment, where you can drive innovation through scientific inquiry, and provide tangible benefit to hundreds of thousands of our associates worldwide, this is your opportunity. Come work on the Amazon Worldwide Fulfillment Design & Engineering Team! We are looking for an experienced and Research Scientist with background in Ergonomics and Industrial Human Factors, someone that is excited to work on complex real-world challenges for which a comprehensive scientific approach is necessary to drive solutions. Your investigations will define human factor / ergonomic thresholds resulting in design and implementation of safe and efficient workspaces and processes for our associates. Your role will entail assessment and design of manual material handling tasks throughout the entire Amazon network. You will identify fundamental questions pertaining to the human capabilities and tolerances in a myriad of work environments, and will initiate and lead studies that will drive decision making on an extreme scale. .You will provide definitive human factors/ ergonomics input and participate in design with every single design group in our network, including Amazon Robotics, Engineering R&D, and Operations Engineering. You will work closely with our Worldwide Health and Safety organization to gain feedback on designs and work tenaciously to continuously improve our associate’s experience. Key job responsibilities - Collaborating and designing work processes and workspaces that adhere to human factors/ ergonomics standards worldwide. - Producing comprehensive and assessments of workstations and processes covering biomechanical, physiological, and psychophysical demands. - Effectively communicate your design rationale to multiple engineering and operations entities. - Identifying gaps in current human factors standards and guidelines, and lead comprehensive studies to redefine “industry best practices” based on solid scientific foundations. - Continuously strive to gain in-depth knowledge of your profession, as well as branch out to learn about intersecting fields, such as robotics and mechatronics. - Travelling to our various sites to perform thorough assessments and gain in-depth operational feedback, approximately 25%-50% of the time. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
Applied Scientist, EU ATS Science and Tech
DE, BE, Berlin
Have you ever wondered how Amazon delivers timely and reliably hundreds of millions of packages to customer’s doorsteps? Are you passionate about data and mathematics, and hope to impact the experience of millions of customers? Are you obsessed with designing simple algorithmic solutions to very challenging problems? If so, we look forward to hearing from you! Amazon Transportation Services is seeking Applied (or Research) Scientists. As a key member of the central Research Science Team of ATS operations, these persons will be responsible for designing algorithmic solutions based on data and mathematics for optimizing the middle-mile Amazon transportation network. The job is opened in the EU Headquarters in Luxembourg (alternatively: Barcelona, Berlin or London), designed to maximize interaction with the team and stakeholders, but we will consider applicants with remote work requirements as well. Basic qualifications * PhD in Operations Research, Machine Learning, Statistics, Applied Mathematics, Computer Science or other field related to algorithms and data (or equivalent experience). * Excellent written and verbal communication skills. * Experience with some programming language (Java/python/C++) * Research experience in one or more: *Combinatorial optimization problems (e.g., scheduling, vehicle routing, facility location). *Continuous optimization problems (e.g., linear programming, convex programming, non-convex programming). *Predictive analytics (e.g., forecasting, time-series, neural networks) *Prescriptive analytics (e.g., stochastic optimization, bandits, reinforcement learning). Preferred qualifications * Experience from working in a fast-paced applied research environment. * Ability to handle ambiguity. * Top tier publications pertinent to the field of study. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates. Key job responsibilities Solve complex optimization and machine learning problems using scalable algorithmic techniques. Design and develop efficient research prototypes that address real-world problems in the middle-mile operations of Amazon. Lead complex time-bound, long-term as well as ad-hoc analyses to assist decision making. Communicate to leadership results from business analysis, strategies and tactics. A day in the life You will be brainstorming algorithmic approaches with team-mates to solve challenging problems for the middle-mile operations of Amazon. You will be developing and testing prototype solutions with above algorithmic techniques. You will be scavenging information from the sea of Amazon data to improve these solutions. You will be meeting with other scientists, engineers, stakeholders and customers to enhance the solutions and get them adopted. About the team The Science and Tech team of ATS EU is looking for candidates who are looking to impact the world with their mathematical and data-driven skills. ATS stands for Amazon Transportation Service, we are the middle-mile planners: we carry the packages from the warehouses to the cities in a limited amount of time to enable the “Amazon experience”. As the core research team, we grow with ATS business to support decision making in an increasingly complex ecosystem of a data-driven supply chain and e-commerce giant. We schedule more than 1 million trucks with Amazon shipments annually; our algorithms are key to reducing CO2 emissions, protecting sites from being overwhelmed during peak days, and ensuring a smile on Amazon’s customer lips. Our mathematical algorithms provide confidence in leadership to invest in programs of several hundreds millions euros every year. Above all, we are having fun solving real-world problems, in real-world speed, while failing & learning along the way. We use modular algorithmic designs in the domain of combinatorial optimization, solving complicated generalizations of core OR problems with the right level of decomposition, employing parallelization and approximation algorithms. We use deep learning, bandits, and reinforcement learning to put data into the loop of decision making. We like to learn new techniques to surprise business stakeholders by making possible what they cannot anticipate. For this reason, we work closely with Amazon scholars and experts from Academic institutions. We code our prototypes to be production-ready We prefer provably optimal solutions than heuristics, though we settle for heuristics when performance dictates it. Overall, we appreciate the value of correct modeling. We are open to hiring candidates to work out of one of the following locations: Berlin, BE, DEU
Senior Applied Scientist, Applied AI
US, WA, Bellevue
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. On 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. You 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. 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. 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. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
Applied Scientist, Loss Prevention Tech
US, WA, Seattle
Have you ever wanted to solve a mystery or be part of solving a case? Are you fascinated by detective stories or crime shows on TV? Do you love to catch bad actors, build ML models and solve complex problems. If so, working on the Loss Prevention Tech team as a Sr Applied Scientist is the place for you! We detect theft, fraud and organized crime happening across our global supply chain and operations for millions of items, for hundreds of product lines worth billions of dollars of inventory world-wide. We foster new game-changing ideas, creating ever more intelligent and self-learning systems to maximize the cost savings of Amazon's inventory losses. The primary role of a Sr Applied Scientist within Amazon is to address business challenges through building a compelling case, and using data to influence change across the organization. This individual will be given responsibility on their first day to own those business challenges and the autonomy to think strategically and make data driven decisions. Decisions and tools made in this role will have significant impact to the customer experience, as it will have a major impact on all the fraud investigations happening across Amazon operations. Ideal candidates will be a high potential, strategic and analytic graduate with a PhD in ( Research, Statistics, Engineering, and Supply Chain) ready for challenging opportunities in the core of our world class operations space. Great candidates have a history of building fraud detections, detecting organized crime and the ability to use data and research to make changes. This individual will need to be able to work with a team, but also be comfortable making decisions independently, in what is often times an ambiguous environment. Key job responsibilities - Own KPIs that measure fraud management performance and efficiencies. - Detect and automate theft, fraud MOs - Detect organized crime rings and bad actor clusters - Build data or computer vision based ML models - Perform end to end evaluation of operational defects, system gaps, and scaling challenges (both system and operational). - Contribute to the overall fraud management and product development strategies. - Present key learnings and vision to stakeholders and leadership. - Integrate ML detection models via software applications About the team We believe that building a culture that is welcoming and inclusive is integral to people doing their best work and is essential to what we can achieve as a company. We actively recruit people from diverse backgrounds to build a supportive and inclusive workplace. Our team puts a high value on work-live balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
Research Scientist
US, WA, Seattle
Are you interested in working with top talent in Optimization, Operations Research and Supply Chain to help Amazon to efficiently match our Devices with worldwide customers? We have challenging problems and need your innovative solutions to make tremendous financial impacts! The Amazon Devices Science team is looking for a Research Scientist with background in Operations Research, Optimization, Supply Chain and/or Simulation to support science efforts to integrate across inventory management functionalities. Our team is responsible for science models (both deterministic and stochastic) that power world-wide inventory allocation for Amazon Devices business that includes Echo, Kindle, Fire Tablets, Amazon TVs, Amazon Fire TV sticks, Ring, and other smart home devices. We formulate and solve challenging large-scale financially-based optimization problems which ingest demand forecasts and produce optimal procurement, production, distribution, and inventory management plans. In addition, we also work closely with demand forecasting, material procurement, production planning, finance, and logistics teams to co-optimize the inventory management and supply chain for Amazon Devices given operational constraints. Key job responsibilities The successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail, and ability to work in a fast-paced and ever-changing environment and a desire to help shape the overall business. Job responsibilities include: - Design and develop advanced mathematical, simulation, and optimization models and apply them to define strategic and tactical needs and drive appropriate business and technical solutions in the areas of inventory management and distribution, network flow, supply chain optimization, and demand planning - Apply mathematical optimization techniques (linear, quadratic, SOCP, robust, stochastic, dynamic, mixed-integer programming, network flows, nonlinear, nonconvex programming) and algorithms to design optimal or near optimal solution methodologies to be used by in-house decision support tools and software - Research, prototype and experiment with these models by using modeling languages such as Python; participate in the production level deployment - Create, enhance, and maintain technical documentation, and present to other Scientists, Product, and Engineering teams - Support project plans from a scientific perspective by managing product features, technical risks, milestones and launch plans - Influence organization's long-term roadmap and resourcing, and onboard new technologies onto the Science team's toolbox We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
Sr. Applied Scientist, Amazon Robotics (AR)
US, MA, North Reading
Are you excited about developing generative AI and foundation models to revolutionize automation, robotics and computer vision? 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. We are looking for scientists, engineers and program managers for a variety of roles. The Research team at Amazon Robotics is seeking a passionate, hands-on Sr. Applied Scientist to help create the world’s first foundation model for a many-robot system. The focus of this position is how to predict the future state of our warehouses that feature a thousand or more mobile robots in constant motion making deliveries around the building. It includes designing, training, and deploying large-scale models using data from hundreds of warehouses under different operating conditions. This work spans from research such as alternative state representations of the many-robot system for training, to experimenting using simulation tools, to running large-scale A/B tests on robots in our facilities. 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 models About the team You would join our multi-disciplinary science team that includes scientists with backgrounds in 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 them Our 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. We are open to hiring candidates to work out of one of the following locations: North Reading, MA, USA | Westborough, MA, USA
Senior Data Scientist, IPC
US, WA, Bellevue
Inventory Planning and Control (IPC) is seeking an experienced senior data scientist to join its central science team. Our team owns the core decision models in the space of Buying, Placement, and Capacity Control. Our models decide when, where, and how much we should buy, flow, and hold inventories in our global fulfillment network to meet Amazon’s business goals and to make our customers happy. We do this for hundreds of millions of items and hundreds of product lines worth billions of dollars of world-wide for both our Retail and third-party seller business. Our systems are built entirely in-house, for which we constantly develop new technologies in automated inventory planning, prediction, optimization and simulation. Our systems operate at various scales, from real-time decision system that completes thousands of transactions per seconds, to large scale distributed system that optimizes the inventory decisions over millions of products simultaneously. IPC is also unique in that we are simultaneously developing the science and software of inventory optimization and solving some of the toughest computational/operational challenges in production. Our team members 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, scientists, and software engineers in the industry. Key job responsibilities Candidates will be responsible for developing causal, machine learning and data driven models to enhance the various inventory optimization engines that the team owns. The successful candidate should have solid hands-on experience in applying machine learning or causal inference models. They will also be responsible for conducting data driven analysis to facilitate strategic decisions. They require superior logical thinkers who are able to quickly approach large ambiguous problems and develop a practical plan to tackle. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving. They are able to measure and estimate risks, and constructively critique peer research. As a senior scientist, you will also help coach/mentor junior scientists in the team. A day in the life The IPC science team contains a large group of scientists with different technical expertise, who will help and collaborate with you on your projects. In this role, you will also work with our internal customers from the Retail, third-party seller and operations departments worldwide. You will understand their challenges and pain points, and help develop data driven solutions that improve how Amazon manages inventory in our global supply chain. You will work closely with the product managers, engineers and other scientists to turn science proposals into production implementation. About the team We are a team of scientists, product managers and engineers focusing on innovation. We promote experimentation and learn by building. We often tackle the hardest problem in the organization and work cross-functionally. We are at the center of developing inventory solutions to support the rapid growth of Amazon's store business. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA
View from space of a connected network around planet Earth representing the Internet of Things.
Have feedback?
Let us know by taking this short survey
Get started
Amazon.com | Conditions of Use | Privacy | © 1996-2023 Amazon.com, Inc. or its affiliates
Follow Us