stanford-chirpy.jpg
Location: Stanford, CA, USA
Faculty advisor: Christopher Manning

Chirpy Cardinal (2019)

We aim to have a holistic approach towards achieving a multi-turn, on-topic and engaging conversation by designing our systems based on the principles of mixed-initiative.

We are Chirpy Cardinal, a reference to the chirpy colourful bird that shares its name with the ofiicial color and also the names of sports teams at Stanford. Our vision is to create a responsive, empathetic and informative socialbot. We aim to have a holistic approach towards achieving a multi-turn, on-topic and engaging conversation by designing our systems based on the principles of mixed-initiative. Stanford NLP has a strong track record of participating in competitions and shared-tasks, pushing the boundraies of what is considered possible. We are excited to be part of Alexa Prize and bring to bear novel research towards open-domain dialog with real people.

Inside Stanford NLP’s Alexa Prize chatbot: Chirpy Cardinal

Ashwin P. - Team leader

Ashwin is currently a third year Ph.D. student advised by Prof. Chris Manning in the broad area of NLP and Deep Learning. His research focus has been about incorporating structure into language, specifically language models. Going forward, he would like to explore new research questions about conversational AI. Prior to Ph.D., Ashwin did his masters at Stanford working with Prof. Jure Leskovec on data mining, link prediction and graph algorithms research and hid undergrad at IIT Bombay.

Abigail S.

Abi, co-team leader, is a Ph.D. student in the Stanford Natural Language Processing group, where she works on understanding and improving Deep Learning methods for Natural Language Generation. She has interned at Google and Facebook AI Research, where she worked on summarization and chitchat dialogue. With her advisor Chris Manning, she is the co-instructor of CS224n, Stanford's NLP and Deep Learning course. She grew up in the UK and studied Mathematics at Cambridge University.

Peng Q.

Peng is a Ph.D. student at Stanford University studying Natural Language Processing. He is enthusiastic about building NLP systems that help us better understand the knowledge hidden in large amounts of text, as well as building these systems to be explainable and scalable. He is also interested in multilingual and interactive NLP systems that make efficient use of annotated data, by making use of priors such as linguistic knowledge.

Kathleen K.

Kathleen is a Master’s student studying Computer Science (with a focus on Artificial Intelligence) at Stanford University. She has her B.S. in Computer Science from Stanford, where she also minored in Theatre.

Kaushik Ram S.

Kaushik grew up with a fascination for numbers which led him to solve Math problems in high-school which then translated to solving problems using artificial intelligence in grad-school. Kaushik hails from the southern part of India and follows cricket actively. He likes hitting the gym, playing badminton and swimming.

Haojun L.

Haojun is a MSCS student at Stanford University. He did his undergrad at UC Berkeley and was a UGSI for 2 years (CS61A woohoo!). Then Haojun worked at AppDynamics for a year before coming back to school. He has filed 2 patents but is now focusing on NLP research and teaching. In his spare time Haojun likes to cycle, sail, and camp. You can find him either on the road, above the sea (mostly), or in the mountains!

Dilara S.

Dilara is broadly interested in Human Centered AI, fusing design thinking principles with the recent advances in AI to create products that put people in the center. She is specifically interested in virtual assistants. She is currently studying Computer Science at Stanford University, where she was a course assistant in CS224n, NLP and Deep Learning course at Stanford.

Amelia H.

Amelia is a Computer Science Master’s student at Stanford University, specializing in artificial intelligence. As an undergraduate at Stanford, she studied the Computer Science theory track. Her research interests include machine vision, neural verification, and natural language processing.

Minh Phu N.

Minh is a computer science major at Stanford University, with research experience in Artificial Intelligence and industry experience in Product Development. Minh loves to work on cool, useful products and solve challenging problems.

Christopher Manning - Faculty advisor

Christopher Manning is a professor of computer science and linguistics at Stanford University and Director of the Stanford AI Lab. He is a leader in applying deep neural networks to Natural Language Processing, including work on tree recursive models, sentiment analysis, neural machine translation and parsing, and the GloVe word vectors. He founded the Stanford NLP group (@stanfordnlp), developed Stanford Dependencies and Universal Dependencies, and manages development of the Stanford CoreNLP software. Manning is an ACM, AAAI, and ACL Fellow, and a Past President of ACL.

Latest news

The latest updates, stories, and more about Alexa Prize.
  • Behnam Hedayatnia
    March 05, 2019
    The 2018 Alexa Prize featured eight student teams from four countries, each of which adopted distinctive approaches to some of the central technical questions in conversational AI. We survey those approaches in a paper we released late last year, and the teams themselves go into even greater detail in the papers they submitted to the latest Alexa Prize Proceedings. Here, we touch on just a few of the teams’ innovations.
  • Anushree Venkatesh
    February 27, 2019
    To ensure that Alexa Prize contestants can concentrate on dialogue systems — the core technology of socialbots — Amazon scientists and engineers built a set of machine learning modules that handle fundamental conversational tasks and a development environment that lets contestants easily mix and match existing modules with those of their own design.
US, NY, New York
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US, NY, New York
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center at AWS is a new strategic team that helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Data Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. This position requires that the candidate selected be a US Citizen. Key job responsibilities As an Data Scientist, you will - Collaborate with AI/ML scientists and architects to Research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges - Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder - Provide customer and market feedback to Product and Engineering teams to help define product direction A day in the life About AWS Diverse Experiences AWS 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 Culture Here 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 Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
US, WA, Seattle
Device Economics is looking for a senior economist experienced in causal inference, machine learning, empirical industrial organization, and scaled systems to work on business problems to advance critical resource allocation and pricing decisions in the Amazon Devices org. Senior roles lead vision setting, methods innovation, and act as thought leaders to Devices finance and business executives. Output will be included in scaled systems to automate existing processes and to maximize business and customer objectives. Amazon Devices designs and builds Amazon first-party consumer electronics products to delight and engage customers. Amazon Devices represents a highly complex space with 100+ products across several product categories (e-readers [Kindle], tablets [Fire Tablets], smart speakers and audio assistants [Echo], wifi routers [eero], and video doorbells and cameras [Ring and Blink]), for sale both online and in offline retailers in several regions. The space becomes more complex with dynamic product offering with new product launches and new marketplace launches. The Device Economics team leads in analyzing these complex marketplace dynamics to enable science-driven decision making in the Devices org. Device Economics achieves this through scientific applications that provide deep understanding of customer preferences. Our team’s outputs inform product development decisions, investments in future product categories, and product pricing and promotion. We have achieved substantial impact on the Devices business, and will achieve more. Device Economics seeks an experienced economist adept in measuring customer preferences and behaviors with proven capacity to innovate, scale measurement, drive rigor, and mentor talent. The candidate will work with Amazon Devices science leadership to refine science roadmaps, models, and priorities for innovation and simplification, and advance adoption of insights to influence important resource allocation and prioritization decisions. Effective communication skills (verbal and written) are required to ensure success of this collaboration. The candidate must be passionate about advancing science for business and customer impact.
US, WA, Seattle
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. On Prime Video, customers can find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies Road House, The Lord of the Rings: The Rings of Power, Fallout, Reacher, The Boys, and The Idea of You; licensed fan favorites Dawson’s Creek and IF; Prime member exclusive access to coverage of live sports including Thursday Night Football, WNBA, and NWSL, and acclaimed sports documentaries including Bye Bye Barry and Federer; and programming from partners such as Apple TV+, Max, Crunchyroll, and MGM+ via Prime Video add-on subscriptions, as well as more than 500 free ad-supported (FAST) Channels. Prime members in the U.S. can share a variety of benefits, including Prime Video, by using Amazon Household. Prime Video is one benefit among many that provides savings, convenience, and entertainment as part of the Prime membership. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles, including blockbusters such as Challengers and The Fall Guy, via the Prime Video Store, and can enjoy content such as Jury Duty and Bosch: Legacy free with ads on Freevee. Customers can also go behind the scenes of their favorite movies and series with exclusive X-Ray access. For more info visit www.amazon.com/primevideo. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities As a Research Scientist at Prime Video, you will have end-to-end ownership of the product, related research and experimentation, applying advanced machine learning techniques in computer vision (CV), natural language processing (NLP), multimedia understanding and so on. You’ll work on diverse projects that enhance Prime Video’s recommendation systems, image/video understanding, and content personalization, driving impactful innovations for our global audience. Other responsibilities include: • Lead cutting-edge research in computer vision and natural language processing, applying it to video-centric media challenges. • Develop scalable machine learning models to enhance media asset generation, content discovery, and personalization. • Collaborate closely with engineering teams to integrate your models into production systems at scale, ensuring optimal performance and reliability. • Actively participate in publishing your research in leading conferences and journals. • Lead a team of skilled research scientists, you will shape the research strategy, create forward-looking roadmaps, and effectively communicate progress and insights to senior leadership • Stay up-to-date with the latest advancements in AI and machine learning to drive future research initiatives.
IL, Haifa
AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Are you an inventive, curious, and driven Applied Scientist with a strong background in AI and Deep Learning? Join Amazon’s AWS Multimodal generative AI science team and be a catalyst for groundbreaking advancements in Computer Vision, Generative AI, and foundational models. As part of the AWS Multimodal generative AI science team, you’ll lead innovative research projects, develop state-of-the-art algorithms, and pioneer solutions that will directly impact millions of Amazon customers. Leveraging Amazon’s vast computing power, you’ll work alongside a supportive and diverse group of top-tier scientists and engineers, contributing to products that redefine the industry. Key job responsibilities * Lead research initiatives in Multimodal generative AI, pushing the boundaries of model efficiency, accuracy, and scalability. * Design, implement, and evaluate deep learning models in a production environment. * Collaborate with cross-functional teams to transfer research outcomes into scalable AWS services. * Publish in top-tier conferences and journals, keeping Amazon at the forefront of innovation. * Mentor and guide other scientists and engineers, fostering a culture of scientific curiosity and excellence. About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture: Here 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 Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why 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.
AU, NSW, Sydney
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. The Generative Artificial Intelligence (AI) Innovation Center team at AWS provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies leveraging cutting-edge generative AI algorithms. As an Applied Scientist, you'll partner with technology and business teams to build solutions that surprise and delight our customers. We’re looking for Applied Scientists capable of using generative AI and other ML techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities - Collaborate with scientists and engineers to research, design and develop cutting-edge generative AI algorithms to address real-world challenges - Work across customer engagement to understand what adoption patterns for generative AI are working and rapidly share them across teams and leadership - Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths for generative AI - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder - Provide customer and market feedback to Product and Engineering teams to help define product direction. A day in the life Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. 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. About the team Diverse Experiences AWS 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 Culture Here 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 Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why 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. What if I don’t meet all the requirements? That’s okay! We hire people who have a passion for learning and are curious. You will be supported in your career development here at AWS. You will have plenty of opportunities to build your technical, leadership, business and consulting skills. Your onboarding will set you up for success, including a combination of formal and informal training. You’ll also have a chance to gain AWS certifications and access mentorship programs. You will learn from and collaborate with some of the brightest technical minds in the industry today.
US, NY, New York
Interested in building something new? Join the Amazon Autos team on an exhilarating journey to redefine the vehicle shopping experience. This is an opportunity to be part of the ground floor team for one of Amazon's new business ventures. As a key member, you'll lead the science strategy and play a pivotal role in helping us achieve our mission. Our goal is to create innovative automotive discovery and shopping experiences on Amazon, providing customers with greater convenience and a wider selection. If you're enthusiastic about innovating and delivering exceptional shopping experiences to customers, thrive on new challenges, and excel at solving complex problems using top-notch ML models, LLM and GenAI techniques, then you're the perfect candidate for this role. Strong business acumen and interpersonal skills are a must, as you'll work closely with business owners to understand customer needs and design scalable solutions. Join us on this exhilarating journey and be part of redefining the vehicle shopping experience. Key job responsibilities As Senior Applied Scientist in Amazon Autos, you will: - Lead the roadmap and strategy for applying science to solve customer problems in the Amazon AutoStore domain. - Drive big picture innovations with clear roadmaps for intermediate delivery. - Determine which areas of research to invest in. - Effectively communicate complicated machine learnings concepts to multiple partners. - Identify when to leverage existing technology versus innovate a new technology. - Work closely with partners to identify problems from the customer's perspective. - Interface with business customers, gathering requirements and delivering science solutions. - Apply your skills in areas such as deep learning and reinforcement learning while building scalable solutions for business problems. - Produce and deliver models that help build best-in-class customer experiences and build systems that allow us to deploy these models to production with low latency and high throughput. - Utilize your Generative AI, time series and predictive modeling skills, and creative problem-solving skills to drive new projects from ideation to implementation. - Establish scalable, efficient, automated processes for large scale data analyses, model development, validation and implementation. We are looking for a Senior Applied Scientist who loves working with big data and is passionate about improving the customer shopping experience. A day in the life In this role, you will be part of a multidisciplinary team working on one of Amazon's newest business ventures. As a key member, you will collaborate closely with engineering, product, design, operations, and business development to bring innovative solutions to our customers. Your science expertise will be leveraged to research and deliver novel solutions to existing problems, explore emerging problem spaces, and create new knowledge. You will invent and apply state-of-the-art technologies, such as large language models, machine learning, natural language processing, and computer vision, to build next-generation solutions for Amazon. You'll publish papers, file patents, and work closely with engineers to bring your ideas to production. Additionally, you will mentor Applied Scientists and Software Development Engineers with an interest in machine learning. This is an opportunity to make a significant impact, working in partnership with teams across Amazon to create enormous benefits for our customers through cutting-edge products. About the team This is a critical role for a newly formed team with a vision to create innovative automotive discovery and shopping experiences on Amazon, providing customers better convenience and more selection. We’re collaborating with other experienced teams at Amazon to define the future of how customers research and shop for cars online.
US, WA, Seattle
Enterprise Engineering is seeking an exceptional Senior Applied Scientist to join our AppSense team, which is revolutionizing Software Asset Management at Amazon and beyond. As a key member of our applied science team, you will leverage cutting-edge machine learning, natural language processing, and data analytics techniques to solve complex challenges in software discovery, cost optimization, and intelligent decision-making. Your work will directly impact Amazon's ability to manage its vast software portfolio efficiently, driving significant cost savings and operational improvements. In this role, you will have the opportunity to invent and implement novel scientific approaches that address critical business problems at the product level. You will collaborate closely with product managers, engineers, and business stakeholders to translate scientific innovations into practical, scalable solutions that enhance AppSense's capabilities and deliver value to our customers. Key job responsibilities * Lead the design, implementation, and delivery of scientifically complex solutions for AppSense, focusing on areas such as automated software discovery, intelligent cost optimization, and predictive analytics * Develop and apply state-of-the-art machine learning models to improve software categorization, usage prediction, and anomaly detection * Create innovative natural language processing solutions for contract analysis, optimization, and automated report generation * Design and implement advanced recommendation systems for software stack optimization based on job roles and team compositions * Develop reinforcement learning algorithms for automated license management, including predictive maintenance to prevent unexpected expirations or overage charges * Develop AI-driven negotiation assistants and collaborative budgeting tools with ML-powered spend forecasting * Create sentiment analysis models to gauge software satisfaction from user feedback and support tickets About the team The AppSense team is at the forefront of transforming software asset management at Amazon. We're building a comprehensive platform that provides visibility, control, and optimization for Amazon's vast software portfolio. Our mission is to leverage cutting-edge technology to help businesses discover, manage, and optimize their software assets, driving significant cost savings and operational efficiencies. As part of the applied science team within AppSense, you'll work alongside talented scientists, engineers, and product managers who are passionate about solving complex problems at scale. We foster a culture of innovation, encouraging team members to push the boundaries of what's possible in software asset management. Your contributions will directly impact Amazon's bottom line and have the potential to shape the future of how organizations manage their software ecosystems.
US, WA, Seattle
** This position is open to all candidates in Palo Alto, CA, Seattle, WA, NYC and Arlington, VA ** Amazon Ads Response Prediction team is your choice, if you want to join a highly motivated, collaborative, and fun-loving team with a strong entrepreneurial spirit and bias for action. We are seeking an experienced and motivated Machine Learning Applied Scientist who loves to innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems. Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. We are looking for a talented Machine Learning Applied Scientist for our Amazon Ads Response Prediction team to grow the business. We are providing advanced real-time machine learning services to connect shoppers with right ads on all platforms and surfaces worldwide. Through the deep understanding of both shoppers and products, we help shoppers discover new products they love, be the most efficient way for advertisers to meet their customers, and helps Amazon continuously innovate on behalf of all customers. Key job responsibilities As a Machine Learning Applied Scientist, you will: * 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 business About the team We are pioneers in applying advanced machine learning and generative AI algorithms in Sponsored Products business. We empower every customer with a customized discovery experiences from back-end optimization (such as customized response prediction models) to front-end CX innovation (such as widgets), to help shoppers feel understood and shop efficiently on and off Amazon.
US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the extreme. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.