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Amazon SageMaker Debugger: A system for real-time insights into machine learning model training

By Nathalie Rauschmayr, Vikas Kumar, Rahul Huilgol, Andrea Olgiati, Satadal Bhattacharjee, Nihal Harish, Vandana Kannan, Amol Lele, Anirudh Acharya, Jared Nielsen, Lakshmi Ramakrishnan, Ishaaq Chandy, Ishan Bhatt, Zhihan Li, Kohen Chia, Neelesh Dodda, Jiacheng Gu, Miyoung Choi, Balajee Nagarajan, Jeffrey Geevarghes, Denis Davydenko, Sifei Li, Lu Huang, Edward Kim, Tyler Hill, Krishnaram Kenthapadi
2021
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Manual debugging is a common productivity drain in the machine learning (ML) lifecycle. Identifying underperforming training jobs requires constant developer attention and deep domain expertise. As state-of-the-art models grow in size and complexity, debugging becomes increasingly difficult. Just as unit tests boost traditional software development, an automated ML debugging library can save time and money. We present Amazon SageMaker Debugger, a machine learning feature that automatically identifies and stops underperforming training jobs. Debugger is a new feature of Amazon SageMaker that automatically captures relevant data during training and evaluation and presents it for online and offline inspection. Debugger helps users define a set of conditions, in the form of built-in or custom rules, that are applied to this data, thereby enabling users to catch training issues as well as monitor and debug ML model training in real-time. These rules save time and money by alerting the developer and terminating a problematic training job early.
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Senior Applied Scientist, Amazon
US, NY, New York
We are seeking a motivated and experienced Senior Applied Scientist with expertise in Machine Learning (ML), Artificial Intelligence (AI), Big Data, and Service Oriented Architecture. You should have a deep understanding of the digital advertising business and scaled marketing across communication channels. In this role, you will collaborate with a cross-functional team of talented scientists and engineers to innovate, iterate, and solve real-world marketing problems with cutting-edge AWS technologies. You will lead in-depth analyses of the key problems faced by Amazon Ads customers and the challenges faced by marketing teams in meeting customer needs at scale. To address these problems, you will build innovative large-scale ML/AI solutions such as bespoke omni-channel recommender systems, and specialized LLM-powered assistants for customers and marketers. You will independently drive research and prototyping to deliver functional proofs of concept (POCs), and then partner with engineers to inform the technology roadmap and deploy successful POCs as scalable batch and real-time applications in production. Key job responsibilities • Define and execute a research and development plan that enables data-driven marketing decisions and delivers inspiring customer experiences • Evaluate, evolve, and invent scientific techniques to effectively address customer needs and business problems • Establish and drive science prototyping best practices to ensure coherence and integrity of data feeding into production ML/AI solutions • Collaborate with colleagues across science and engineering disciplines for rapid prototyping at scale • Partner with engineering teams to solve complex technical problems, define system-level requirements, develop implementation plans, and guide the adaptation of techniques to meet production needs • Partner with product managers and stakeholders to define forward-looking product visions and prospective business use-cases • Drive and lead of culture of data-driven innovation within and outside across Amazon Ads Marketing organization • Influence organizational vision across Ads Marketing organization About the team The Marketing Decisions Science team provides AI/ML products to enable Amazon Ads Marketing to deliver relevant and compelling guidance, education, and inspiration to prospective and active advertisers across marketing channels. We own the product, technology, and deployment roadmap for AI/ML products across Amazon Ads Marketing. We analyze the needs, experiences, and behaviors of Amazon advertisers at petabytes scale, to deliver the right marketing communications to the right advertiser at the right time. Our products enable applications and synergies across Ads organization, spanning marketing, product, and sales use cases.
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US, NY, New York
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Senior Economist, Device Economics
US, WA, Seattle
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US, WA, Seattle
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Applied Scientist , Gen AI
IL, Haifa
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Applied Scientist, Generative Artificial Intelligence (AI) Innovation Center
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.
Sr. Applied Scientist, Amazon Autos
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.
Applied Scientist, Enterprise Engineering
US, WA, Seattle
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Applied Scientist , Sponsored Products Ads Response Prediction
US, WA, Seattle
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Sr. Research Scientist, Special Projects
US, WA, Seattle
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