Using lightweight formal methods to validate a key-value storage node in Amazon S3

2021
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This paper reports our experience applying lightweight formal methods to validate the correctness of ShardStore, a new key-value storage node implementation for the Amazon S3 cloud object storage service. By “lightweight formal methods" we mean a pragmatic approach to verifying the correctness of a production storage node that is under ongoing feature development by a full-time engineering team. We do not aim to achieve full formal verification, but instead emphasize automation, usability, and the ability to continually ensure correctness as both software and its specification evolve over time. Our approach decomposes correctness into independent properties, each checked by the most appropriate tool, and develops executable reference models as specifications to be checked against the implementation. Our work has prevented 16 issues from reaching production, including subtle crash consistency and concurrency problems, and has been extended by non-formal-methods experts to check new features and properties as ShardStore has evolved.
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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! The Measurement Science team delivers campaign measurement and reporting across Amazon Advertising businesses and serves as the scientific center of excellence for algorithm development in campaign measurement. Programs supported by our services include Sponsored Products, Sponsored Brands, Sponsored Display, Amazon DSP for Display, Video and Audio advertising, 3P Paid Merchandising (HOTW), Amazon Live, and others. Our measurement engineering platforms and products deliver campaign performance reporting to advertisers. This includes development and management of: our compute infrastructure; ad server logs, identities, conversion events, and campaign dimension ingestion; advertising facts aggregation at scale; attribution processing; measurement of complex campaign calculations such as unique reach and frequency; interactive dash-boarding infrastructure; campaign reporting applications for display advertising programs; and data warehousing of advertising aggregates for business intelligence. We show ads on and off our site, effectively measuring the internet with billions of incoming, highly decorated events to process and summarize every day in near real time. Our infrastructure is extreme scale, requiring invention ahead of common technologies and exceeding the scale of most of Amazon services (>1mm TPS, PB-scale). Key job responsibilities * Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. * Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. * Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. * Run A/B experiments, gather data, and perform statistical analysis. * Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. * Research new and innovative machine learning approaches. * Recruit Scientists to the team and provide mentorship. 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 scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. A day in the life About the team 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. Team video https://youtu.be/zD_6Lzw8raE We are open to hiring candidates to work out of one of the following locations: Toronto, ON, CAN
US, NY, New York
Amazon is investing heavily in building a world class advertising business and we are responsible for 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. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities. We are looking for a Data Scientist/Applied Scientist to join Search Product Discovery team in Marketplace Intelligence with a broad mandate to experiment and innovate to grow Sponsored Products. As an Applied Scientist in this team, you will help to identify unique opportunities to create customized and delightful shopping experience for our growing marketplaces worldwide. You will play a crucial role in enriching the diversity of Amazon's search page to improve the shopping experience for our customers. Your primary focus will be harnessing your analytical skills to establish diversity metrics, conduct in-depth research into how diversity influences shopper behavior, and construct a comprehensive framework to enhance product diversity through ad ranking and allocation on the search page. Key job responsibilities - Be the technical leader in statistical methods and Machine Learning; lead efforts within this team and across other teams. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Research new and innovative machine learning approaches. - Recruit Scientists to the team and provide mentorship. We are open to hiring candidates to work out of one of the following locations: New York, NY, USA
US, NY, New York
The Data Science Manager will be a key leadership member the Credit team in Amazon Business Payments and Lending. This leader will lead the science team developing best-in-class underwriting systems. This role presents a significant intellectual, technical, and operational challenge with enormous opportunity for business impact. Amazon is dedicated to building credit/lending services that help small, medium, and large businesses worldwide. We believe we are in a unique position to serve our customers with exceptional value due to our deep understanding and insight into our base coupled with rigorous scientific approach and customer-focused emphasis to building financial products. This leader will be passionate about enabling the growth of small, medium, and large businesses and other to-be-launched segments by removing a critical barrier to deepening their activity on Amazon – access to capital. This leader will demonstrate high judgment and deep business experience across economic cycles. They will bring proven ability to identify and recommend data-driven solutions, navigating through complex financial and regulatory issues across geographies. This role is highly strategic and will interact with all levels across a broad range of teams and leaders across Amazon. This leader will need to work with our business and product management partners to communicate the properties of their team’s analysis/modeling. This leader owns the multi-year research agenda and prioritization for the team, and ensure that projects meaningful drive results. Key job responsibilities · Lead, mentor, and develop a top-performing data science team · Apply advanced analytics and ML techniques to support Credit Management processes · Source, incorporate, and analyze alternative credit data to drive innovation · Own data science team roadmap, balance multiple projects efficiently and achieve goals in a fast-paced, dynamic environment · Collaborate effectively with Credit Strategy, operation, product teams, and senior management at ABPL to underwrite new customers and manage portfolio risk · Enhance operating efficiencies and excellence, ensure high performant credit management science models · Promote a culture of transparency, integrity, and ethical use of data. We are open to hiring candidates to work out of one of the following locations: New York, NY, USA | Seattle, WA, USA
IN, KA, Bangalore
The Generative 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. Here at AWS, we welcome all builders. We believe that technology should be built in a way that’s inclusive, accessible, and equitable. We’re committed to putting in the work for more equal representation 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. About the team You will work with a diverse team of Architects, ML Scientists, and Strategists to help and guide AWS customers across Asia Pacific, Japan, China and India in their journey to adopt generative AI. We are open to hiring candidates to work out of one of the following locations: Bangalore, KA, IND | Mumbai, MH, IND
TW, TPE, Taipei
Amazon Lab126 is an inventive research and development company that designs and engineers high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating the best-selling Kindle family of products. Since then, we have produced groundbreaking devices like Fire tablets, Fire TV, and Amazon Echo. What will you help us create? Key job responsibilities You will be working on developing Computer Vision algorithms to improve deep learning models including reducing the sample complexity, improving generalization ability, boosting model robustness, etc. You will be a critical science contributor and can create a significant business impact to the company. This opportunity requires excellent technical, problem-solving, and communication skills. An ideal candidate will have a high teamwork mentality coupled with a strong bias for action yet always insisting on the highest standards. We also aim to publish our innovation and findings to computer vision top conferences including CVPR, ICCV, ECCV. A day in the life In this role, you will work closely with other researchers in the team to research, design, and deliver science components powering computer vision and active learning algorithms to cost-effectively create very large-scale training datasets for various computer vision/robotics applications. You will have the unique opportunity to work on multiple popular Computer Vision tasks altogether, therefore, embrace the great potential to innovate more. About the team We are a smart team of doers that work passionately to apply cutting-edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. The team is using computer vision, machine learning, sensor fusion, real-time and distributed systems to convert requirements into concrete deliverables. A Researcher on this team will translate business and functional requirements into working code. Comfort with a high degree of ambiguity and ability to solve problems that haven’t been solved to scale before are essential. We are open to hiring candidates to work out of one of the following locations: Hsinchu City, TPE, TWN | Taipei, TPE, TWN