Rajeev Rastogi headshot with map of India
Rajeev Rastogi, vice president of machine learning for Amazon India, and his team work to address the needs of more than 600 million people who are online, who together speak more than 22 languages and 19,500 dialects.
Credit: Glynis Condon

How Rajeev Rastogi’s machine learning team in India develops innovations for customers worldwide

Team works to address the needs of 600 million people online who together speak more than 22 Indian languages with over 19,500 dialects.

As vice president of machine learning at Amazon India, Rajeev Rastogi is helping his team drive innovations that have a profound impact not only on shoppers in India, but also on the company’s customers around the world. For example, models developed by Amazon’s scientists in India have been used globally to improve the quality of Amazon’s catalog by ensuring that for all products, images match with the title. In addition, including delivery speed as a feature in search ranking — a key factor that helps surface ‘faster’ offers to customers in search results — was first launched in Amazon India.

Rastogi began his career at Bell Labs. His early work involved developing clustering algorithms that could scale — a significant innovation in a field that was then dominated by statisticians working on relatively smaller data sets. Rastogi also served as the vice president of Yahoo Labs, where his team developed data-extraction algorithms to pull structured information from billions of webpages, and then present them to users in easily digestible ways.

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Rastogi joined Amazon in 2012. His first Amazon project involved the development of algorithms to classify products into Amazon’s large and complex taxonomical structure — for example, to classify a Samsonite luggage set in ‘Carry-On Luggage,’ ‘Suitcases’ and ‘Luggage Sets.’ Since then, Rastogi has been involved in utilizing science to make an impact in a number of areas that have resulted in faster, more seamless and sustainable, shopping experiences.

In this interview, Rastogi spoke about the projects his teams have worked on to improve the shopping experience for Amazon’s customers, a recently developed statistical model that has helped Amazon reduce product-shipment damage in India, and innovations developed to help customers get what they need safely after the outbreak of the COVID-19 pandemic.

Q. What are some of the ways that science has helped improve the shopping experience for Amazon’s customers in India?

India is a unique market in several important ways. There are more than 600 million people online in the country. Many of them are relatively new to digital shopping. Over 85% of our traffic comes from a diverse range of mobile devices.  To complicate matters, mobile customers in India can experience fluctuating speeds due to congested towers and tower switching.

We’ve developed models to predict customers who are on a slow or spotty network based on criteria like device characteristics, cell tower information, and the latency of the last request. For such customers, we provide an adaptive experience and serve streamlined pages with a lower number of widgets that are easier to navigate.

With more than 22 languages and 19,500 dialects, India is also an incredibly diverse country with strong regional preferences. A customer searching for a sari in Gujarat may be interested in a “Bandhani,” which is popular in that state, while a customer in Karnataka searching for a sari may be looking for “Mysore Silk,” a popular variety in that region. To surface regionally popular and relevant products in search results, we have added regional sales for products as a feature in search.

A key problem in India and other emerging countries is that addresses are highly unstructured; they are also incomplete, with critical address fields such as street name missing from the address. For example, we have seen addresses on Amazon.in such as “Near Orion Mall, Malleswaram, Bangalore”, or “Near Bus Stand, Sambhaji Chowk, Nasik”. Our team has developed a machine-learning-based “Address Deliverability Score” to identify poor quality and incomplete addresses that are difficult to locate and deliver to, and intercept them at address creation time to improve address quality.  

You can also have issues related to catalog quality. For example, important attribute values such as the color of a product may be missing for a product. This means that a shoe might be red, and yet might not show up in the list of results for a customer searching for ‘red shoe.’

We use a variety of deep learning models to improve catalog quality by extracting attributes such as color from product titles and images, and backfilling missing product information. To give just one example, we use attention mechanisms to focus the attention of convolutional neural networks on parts of the image from where we want to extract the color of a product. 

We also utilize semi-supervised learning techniques to train neural networks extensively, which greatly reduces the need for large amounts of labeled data. What I love about this approach is that unlabeled data can be a treasure trove of information, particularly for understanding higher-level representations. For example, an algorithm can analyze text patterns around words to understand that ‘car’ and ‘automobile’ are similar without having to explicitly specify that they are synonyms.

India is a market unlike any other in the world, and I’m proud of how we are using science to solve some really difficult problems for our customers.

Q. How are you using science to make Amazon more sustainable?

Amazon has committed to reach net zero carbon by 2040, one decade ahead of the Paris Agreement. Science will play an extremely important role in enabling innovations that will make this happen.

Let me give you just one example. At this year’s European Conference on Machine Learning, members of my team presented a new model for determining the best way to package a given product. We’ve all seen customers not happy about damaged products and excessive product packaging. Incorrect packaging is not only wasteful and bad for the environment, but it also increases our packaging and concessions costs.

India is a market unlike any other in the world, and I’m proud of how we are using science to solve some really difficult problems for our customers.
Rajeev Rastogi

Determining the optimal way to ship a product is complicated. Because one product is rarely shipped across all different package types, you run into situations where there’s a lack of ground truth data. In addition, we have the problem of enforcing ordinality into the process. We have to predict higher probabilities of damage for less expensive (less robust) packaging options, and lower probabilities of damage for more expensive (more robust) options. Enforcing ordinality is not something that standard machine learning techniques do naturally.

The solution developed by my team is as elegant as it is simple. Our scientists developed a linear model, with carefully designed constraints on the model parameters to impose ordinality. To further enforce ordinality, we used data augmentation. This means that for a product-package pair that resulted in product damage, we added examples of that product coupled with less robust packages, also labeled as resulting in damage. 

We’ve applied the model to hundreds of thousands of Amazon packages, reducing shipment damage very significantly while actually saving on shipping costs. This innovation is a testament to the incredible scientific talent at Amazon India. It also speaks volumes of our desire and our ability to take on the really big problems — those that have a significant impact on the lives of our customers and the world at large.

Q. What are some scientific innovations from your team to help customers get what they need safely during COVID-19?

As soon as the pandemic struck, I became interested in what we could do as scientists to keep people safe, and help them get what they need during these trying times. Could we use technology to generate an infection risk score for each individual? These scores could be leveraged by governments and organizations to prioritize testing and identify individuals to quarantine.

We all know that COVID-19 spreads through contacts. Many governments have developed contact tracing apps that use Bluetooth signals on mobile phones to track social contacts among individuals. However, it is challenging to use this fine-grained contact data of individuals to estimate an infection risk score for each individual. This is because the probability of infection transmission through a contact depends on the duration, distance, and location (indoors, outdoors) of the contact. Furthermore, individuals may have indirectly come in contact with a person who has tested positive for COVID-19. Or they may have come in contact with an infected person, but during the period when he or she was not contagious.

I worked with fellow scientists to develop a probabilistic graphical model called CRISP for COVID-19 infection spread through contacts between individuals. The model builds off the SEIR (Susceptible-Exposed-Infectious-Removed) approach that is commonly used to track the different epidemiological status of individuals. Our model captures the transitions between these different states, while also accounting for test outcomes. We developed a block-Gibbs sampling algorithm to draw samples of the latent infection status of each individual, given data about contacts and test results. These infection status samples are then used to compute infection risk scores for each individual. We also developed a Monte Carlo Expectation Maximization (EM) algorithm to infer the infection transmission probability for each contact taking into account factors such as contact duration, distance, and location.  

Also during the pandemic, our operations team built virtual pickup points to deliver packages to customers who live in quarantined apartment buildings. The problem: identifying customers who live in these buildings and educating them about the virtual pickup points. We used address segmentation machine learning models to extract apartment building names from delivery addresses input by customers. We then sent emails to these customers notifying them about the new features. Customers were really excited about this new feature — the email open rates announcing virtual pickup points were higher than 50%.

I’ve been at Amazon for eight years now. I joined Amazon because I was excited at the prospect of conducting scientific work that had the potential to have a real-world impact. And what was true back then remains true today — I come to work every day invigorated at the potential of making a difference in the lives of millions of people around the world.

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Take the earth's most customer-centric company. Mix in millions ofshoppers spending billions of dollars annually and an opportunity to useyour skills in machine learning and data mining to improve productrecommendations and search. What do you get? The best job in theinternet today - PERIOD.The charter of Amazon’s Personalization team is to recommend the “right" product to the “right" customer at the “right" time. We generatepersonalized product recommendations for millions of customers each day, in a blink of an eye, thousands of times a second.If you are a strong software engineer with a background in MachineLearning, who is passionate about turning massive amounts of data intoactionable insights, then this is the right opportunity for you.You will work with a team of highly skilled and motivated scientists andengineers, who are building the next generation of personalizationproducts at Amazon. Our team advances the state-of-the-art inpersonalization by using machine learning, and leveraging Amazon’s vast computing resources (AWS) and data. As part of your job, you will deal with large amounts of training data, rapidly prototype new models that meet stringent performance requirements, and perform offline and online testing.Major responsibilities:- Research and use of statistical techniques to create scalablesolutions for business problems- Analyze and extract relevant information from large amounts ofAmazon's historical business data to help automate and optimize keyfeatures and processes- Work closely with scientists and engineering teams to create anddeploy new features- Work closely with stakeholders to optimize various business operations- Establish scalable, efficient, automated processes for large scaledata analyses, model development, validation and implementation.- Track general business activity and provide clear, compellingmanagement reporting on a regular basisBy submitting your application here, you can apply once to be considered for multiple Software Engineering openings across various Amazon teams. If you are successful in passing through the initial application review and assessment, you will be asked to submit your career and personal preferences so that our dedicated recruiters can match you to the right role based on these preferences.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/usAmazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual OrientationBy submitting your application here, you can apply once to be considered for multiple Software Engineering openings across various Amazon teams. If you are successful in passing through the initial application review and assessment, you will be asked to submit your career and personal preferences so that our dedicated recruiters can match you to the right role based on these preferences.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/usAmazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
US, WA, Seattle
Amazon Business (www.amazon.com/business) is an online store that combines the selection, convenience and value customers have come to know and love from Amazon, with new features and unique benefits tailored to the needs of businesses. Amazon Business provides easy access to hundreds of millions of products – everything from IT and lab equipment to education and food-service supplies. Amazon Business customers also enjoy a variety of benefits, including business-only pricing and selection, a multi-seller marketplace, single- or multi-user business accounts, approval workflow, purchasing system integrations, payment solutions, tax exemptions, dedicated customer support, Business Prime and more.Business Prime is a paid subscription service for verified business, charity or government organizations that provides the familiar Prime shopping experience end users love at home, with pricing plans and benefits that are suited for work. Business Prime now serves over a million employees in organizations throughout the world. Our customers range from government entities with tens of thousands of users to sole proprietors.The Business Prime team is looking for an experienced and motivated Data Scientist to generate data-driven insights influencing the Business Prime direction, build the necessary predictive models, optimization algorithms and customer behavioral segments allowing us to discover and expand the value proposition of Business Prime to the customers. Specific responsibilities include:- Customer lifecycle analysis improving targeting, customer identification, and spend behavior.- Data driven insights to accelerate acquisition of new members.- Grow benefits adoption based on customer segment, vertical, and drive customers to their "aha moment".- Predict customers at risk of churn and declining engagement.- Identify ineligible accounts including fraud, abuse, and other undesired behaviors.- Experiments to enhance membership value for B2B customers.In this role, you will be a technical expert with significant scope and impact. You will work with Business Intelligence Engineers, Financial Analysts, Product Managers, Software Engineers, Data Engineers, and other Data Scientists, to build new and enhance existing ML models to optimize customer experience. The successful Data Scientist will have extreme bias for action needed in a startup environment, with outstanding leadership skills, proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. We are seeking someone who can thrive in a fast-paced, high-energy and fun work environment where we deliver value incrementally and frequently. We value highly technical people who know their subject matter deeply and are willing to learn new areas. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career.
US, WA, Seattle
Amazon strives to be Earth's most customer-centric company. To achieve this, we hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment.Economists for Amazon will be expected to work directly with senior management on key business problems faced in retail and marketing. The role allows you to influence company-wide strategy by applying the frontier of economic thinking to forecasting, program evaluation, customer behavior and other areas. Economists at Amazon will be expected to develop new techniques to process large data sets, use econometric models and methods to address complex problems, design and test hypothesis on customer pain points and key growth ideas and contribute to design of automated systems around the company. Economists in our team will work closely with other research scientists, machine learning experts, and economists globally to design new frameworks for understanding business outcome and what impacts customer experiences. Our economists and scientists work closely with software engineers to put algorithms into practice.We are an interdisciplinary team on the cutting edge of economics, statistical analysis, and machine learning whose mission is to solve AI and ML problems that have high risk with high returns Our team seeks an outstanding econometrician with demonstrated experience tackling large-scale time-series forecasting challenges. We prize creative problem solvers with the ability to adapt and extend cutting-edge forecasting models to the unique and interesting problems we have in measuring customer experiences and Amazon business outcome. Our problems include forecasting key customer experiences metrics at different levels of granularities and explaining the drivers of the changes in these metrics. The ideal candidate combines acumen in statistics and applied time-series modeling to grapple with these and other challenges and guide decision-making at the highest levels of accuracy and model explain-ability.
US, CA, Cupertino
Amazon's Simple Storage Service (S3) offers industry-leading scalability, data availability, security, and performance. S3’s Automated Reasoning Group (S3-ARG) develops and applies automated reasoning techniques to deliver correct, secure, durable, and available distributed systems and storage services. S3 is complex: it consists of over 300 microservices each of which is a distributed system. With a very large number of servers and 10s of millions of requests per second, it is also highly concurrent. S3 has a sizable codebase, developed and maintained by a large team of engineers. Getting such a complex and fast-evolving system right requires developing cutting edge automated reasoning methods that are continuously integrated into the software development process. This is what our team does.We work on techniques ranging from deductive proofs to model checking, from static analysis to runtime verification of protocols. We work both at the design and the code level, and connecting the two is essential for us. We partner with development teams to make sure that our methods are deployed across S3 and that correctness is maintained as the software evolves. We have had significant success with adoption and we are key contributors to recent S3 launches such as strong consistency. We are developing innovative methods all the time. We publish our results at conferences and journals.We are a diverse team and are looking for teammates who are enthusiastic to work on these problems and further the state of the art with us. We are seeking candidates who are deep in one area of expertise but also broad enough to take on the most complex cloud computing challenges. If you are interested in exploring, please e-mail s3-arg-jobs@amazon.com.About UsInclusive Team CultureHere 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 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/Life BalanceOur team puts a high value on work-life 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 offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, WA, Seattle
At Alexa Shopping, we strive to enable shopping in everyday life. We allow customers to instantly order whatever they need, by simply interacting with their Smart Devices such as Amazon Show, Spot, Echo, Dot or Tap. Our Services allow you to shop, no matter where you are or what you are doing, you can go from 'I want that' to 'that's on the way' in a matter of seconds. We are seeking the industry's best to help us create new ways to interact, search and shop. Join us, and you'll be taking part in changing the future of everyday lifeWe are seeking a Data Scientist to be part of the NLU science team for Alexa Shopping. This is a strategic role to shape and deliver our technical strategy in developing and deploying NLU, Machine Learning solutions to our hardest customer facing problems. Our goal is to delight customers by providing a conversational interaction. These initiatives are at the heart of the organization and recognized as the innovations that will allow us to build a differentiated product that exceeds customer expectations. We're a high energy, fast growth business excited to have the opportunity to shape Alexa Shopping NLU is defined for years to come. If this role seems like a good fit, please reach out, we'd love to talk to you.This role requires working closely with business, engineering and other scientists within Alexa Shopping and across Amazon to deliver ground breaking features. You will lead high visibility and high impact programs collaborating with various teams across Amazon. You will work with a team of Language Engineers and Scientists to launch new customer facing features and improve the current features.
US, NY, New York
MULTIPLE POSITIONS AVAILABLEEntity: Amazon Web Services, Inc.Title: Data Scientist ILocation: New York, NYPosition Responsibilities:Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production.Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation #0000
US, WA, Seattle
MULTIPLE POSITIONS AVAILABLEEntity: Amazon.Com Services LLCTitle: Applied ScientistWorksite: Seattle, WAPosition Responsibilities:Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists.Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation #0000
US, CO, Denver
Excited by using massive amounts of data to develop Machine Learning (ML) and Deep Learning (DL) models? Want to help public sector, medical center and non-profit agencies derive business value through the adoption of Artificial Intelligence (AI)? Eager to learn from many different enterprise’s use cases of AWS ML and DL? Thrilled to be key part of Amazon, who has been investing in Machine Learning for decades, pioneering and shaping the world’s AI technology?At Amazon Web Services (AWS), we are helping large enterprises build ML and DL models on the AWS Cloud. We are applying predictive technology to large volumes of data and against a wide spectrum of problems. Our Professional Services organization works together with our AWS customers to address their business needs using AI.AWS Professional Services is a unique consulting team. We pride ourselves on being customer obsessed and highly focused on the AI enablement of our customers. If you have experience with AI, including building ML or DL models, we’d like to have you join our team. You will get to work with an innovative company, with great teammates, and have a lot of fun helping our customers.If you do not live in a market where we have an open Data Scientist position, please feel free to apply. Our Data Scientists can live in any location where we have a Professional Service office.A successful candidate will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term solutions. It will be a person who likes to have fun, loves to learn, and wants to innovate in the world of AI. Major responsibilities include:· Understand the customer’s business need and guide them to a solution using our AWS AI Services, AWS AI Platforms, AWS AI Frameworks, and AWS AI EC2 Instances .· Assist customers by being able to deliver a ML / DL project from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models to deliver business impact to the organization.· Use Deep Learning frameworks like PyTorch, Tensorflow, and MxNet to help our customers build DL models.· Use SparkML and Amazon Machine Learning (AML) to help our customers build ML models.· Work with our Professional Services Big Data consultants to analyze, extract, normalize, and label relevant data.· Work with our Professional Services DevOps consultants to help our customers operationalize models after they are built.· Assist customers with identifying model drift and retraining models.· Research and implement novel ML and DL approaches, including using FPGA.· This position can have periods of up to 10% travel.
US, WA, Seattle
At Alexa Shopping, we strive to enable shopping in everyday life. We allow customers to instantly order whatever they need, by simply interacting with their Smart Devices such as Amazon Show, Spot, Echo, Dot or Tap. Our Services allow you to shop, no matter where you are or what you are doing, you can go from 'I want that' to 'that's on the way' in a matter of seconds. We are seeking the industry's best to help us create new ways to interact, search and shop. Join us, and you'll be taking part in changing the future of everyday lifeWe are seeking a Data Scientist to be part of the Correction and Automated Recovery (CARe) team for Alexa Shopping. Our team focuses on solving the hard problem of recovering from shopping errors in the Alexa pipeline and improve customer CX. The solutions will help address unique shopping challenges and maximize the self-learning benefits for shopping. This is a strategic role to shape and deliver our science strategy in developing and deploying Machine Learning solutions to our hardest customer facing problems. The initiatives are at the heart of the organization and recognized as the innovations that are ground breaking and will allow us to exceed customer expectations. If this role seems like a good fit, please reach out, we'd love to talk to you.This role requires working closely with business, engineering and other scientists within Alexa, Shopping and across Amazon to deliver ground breaking features. You will lead high visibility and high impact programs collaborating with various teams across Amazon. You will work with a team of SDEs and Scientists to launch new customer facing features and improve the current features.
US, MA, Cambridge
The Alexa Artificial Intelligence (AI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background, to help build industry-leading Speech and Language technology.About the hiring groupThe Alexa AI team has a mission to push the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Audio Signal Processing, in order to provide the best-possible experience for our customers.Job responsibilitiesAs an Applied Scientist with the Alexa AI team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.