Author

Amitabh Sinha

Director, Research Science

Latest news

US, VA, Arlington
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through SOTA generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. The Marketplace Intelligence (MI) team is looking for an Applied Science Manager to lead a team of scientists and engineers in building production ML and bandit solutions to customize the search experience. We determine which ads to show in Amazon search, where to place them, how many ads to place, and to which customers. This helps shoppers discover new products while helping advertisers put their products in front of the right customers, aligning shoppers’, advertisers’, and Amazon’s interests. To do this, we apply a broad range of machine learning, causal inference, and optimization techniques to continuously explore, learn, and optimize the allocation and ranking of ads on the search page. We are an interdisciplinary team with a focus on customer obsession and inventing and simplifying. Our primary focus is on improving the SP experience in search by gaining a deep understanding of shopper pain points and developing new innovative solutions to address them. You’ll lead the MI Interleaving team. The Interleaving team’s mission is to personalize and contextualize SP ad allocation on the search page. We do this by modeling shopper responses to the number, placement, and quality of ads. We use online experimentation, simulation, causal modeling, and online feedback to estimate the cost of displacing organic and sponsored content. Then, we incorporate those estimates into ad allocation to deliver an efficient and customized shopping experience for shoppers and improved discoverability and sales for advertisers. You’ll own the experimentation systems, models, and online model serving infrastructure to support these solutions. This is a unique opportunity for someone who wants to have broad business impact, a direct impact on customers and the search experience, build scaled real-time LLM and ML solutions, and lead a cross-functional team. If you are interested in machine learning, bandit learning, building production systems, and leading a team to build these solutions, this role is for you. We’re looking for a leader who can help lay out the vision for the team and grow with it. Key job responsibilities * Lead a team of scientists and engineers in building scalable machine learning solutions. * Develop a vision for contextualizing and personalizing SP ads in Amazon search. * Create, develop, and drive a data-driven product strategy to define the right quantitative measures of shopper impact, using this to evaluate decisions and opportunities. * Tackle and solve challenging science and business problems that balance the interests of advertisers, shoppers, and Amazon. * Own a portfolio of pragmatic long-term investments that drive long-term growth of the ads and retail businesses. * Develop real-time LLM and ML algorithms to allocate billions of ads per day in advertising auctions. * Develop efficient algorithms for multi-objective optimization and AI control methods to find operating points for the ad marketplace then evolve them * Develop scientists and ML engineers around machine learning, economics, and optimization for Advertising.
US, CA, Culver City
MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Data Scientist II Job Location: Culver City, California Job Number: AMZ10564056 Position 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. 40 hours / week, 8:00am-5:00pm, Salary Range: $158,681/year to $184,000/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000
ES, M, Madrid
At Amazon, we are committed to being the Earth’s most customer-centric company. The European International Technology group (EU INTech) owns the enhancement and delivery of Amazon’s engineering to all the varied customers and cultures of the world. We do this through a combination of partnerships with other Amazon technical teams and our own innovative new projects. You will be joining the Tools and Machine Learning (Tamale) team. As part of EU INTech, we tackle complex, high-impact problems at the intersection of e-commerce, AI, and customer experience; going well beyond traditional ML pipelines. Our work spans multiple frontiers: we build GenAI-powered data solutions, enabling scalable and cost-efficient training data generation at Amazon scale. We design and deploy agentic systems for detecting and fixing quality issues across Amazon's retail surfaces. And we develop ranking and recommendation models for Haul shopping experiences. We are looking for a passionate, talented, and inventive Scientist with a strong machine learning background to help build industry-leading machine learning solutions. We strongly value your hard work and obsession to solve complex problems on behalf of Amazon customers. Key job responsibilities We look for applied scientists who possess a wide variety of skills. As the successful applicant for this role, you will with work closely with your business partners to identify opportunities for innovation. You will apply machine learning solutions to automate manual processes, to scale existing systems and to improve catalog data quality, to name just a few. You will work with business leaders, scientists, and product managers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed services. You will be part of team of scientists and engineers working on solving data quality issues at scale. You will be able to influence the scientific roadmap of the team, setting the standards for scientific excellence. You will be working with state-of-the-art models, including image to text, Multimodal LLMs and GenAI. Your work will improve the experience of millions of daily customers using Amazon in Europe and in other regions. You will have the chance to have great customer impact and continue growing in one of the most innovative companies in the world. You will learn a huge amount - and have a lot of fun - in the process!
US, MA, Boston
Our team is involved with pre-silicon design verification for custom IP. A critical requirement of the verification flow is the requirement of legal and realistic stimulus of a custom Machine Learning Accelerator Chip. Content creation is built using formal methods that model legal behavior of the design and then solving the problem to create the specific assembly tests. The entire frame work for creating these custom tests is developed using a SMT solver and custom software code to guide the solution space into templated scenarios. This highly visible and innovative role requires the design of this solving framework and collaborating with design verification engineers, hardware architects and designers to ensure that interesting content can be created for the projects needs. Key job responsibilities Develop an understanding for a custom machine learning instruction set architecture. Model correctness of instruction streams using first order logic. Create custom API's to allow control over scheduling and randomness. Deploy algorithms to ensure concurrent code is safely constructed. Create coverage metrics to ensure solution space coverage. Use novel methods like machine learning to automate content creation. About the team Utility Computing (UC) 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 customers who require specialized security solutions for their cloud services. Annapurna Labs (our organization within AWS UC) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.
CL, Virtual
The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for a Economist II who is able to provide structure around complex business problems, hone those complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with various science, engineering, operations, and analytics teams to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. They will lead teams of researchers to produce robust, objective research results and insights which can be communicated to a broad audience inside and outside of Amazon. The ideal candidate has a PhD in Economics and deep expertise in causal inference and applied econometrics. Experience with large-scale data, proficiency in statistical programming (Python), and familiarity with machine learning methods are a plus. To be successful in this role, you should be comfortable operating with ambiguity, able to independently scope and prioritize research agendas, skilled at influencing decisions through rigorous analysis, and comfortable with using AI tools.
IN, KA, Bengaluru
Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like the Kindle family of products, Fire Tablets, Fire TV, Health Wellness, Amazon Echo & Astro products. This is an exciting opportunity to join Amazon in developing state-of-the-art techniques that bring Gen AI on edge for our consumer products. We are looking for exceptional scientists to join our Applied Science team and help develop the next generation of edge models, and optimize them while doing co-designed with custom ML HW based on a revolutionary architecture. Work hard. Have Fun. Make History. Key job responsibilities - Quantize, prune, distill, finetune Gen AI models to optimize for edge platforms - Fundamentally understand Amazon’s underlying Neural Edge Engine to invent optimization techniques - Analyze deep learning workloads and provide guidance to map them to Amazon’s Neural Edge Engine - Use first principles of Information Theory, Scientific Computing, Deep Learning Theory, Non Equilibrium Thermodynamics - Train custom Gen AI models that beat SOTA and paves path for developing production models - Collaborate closely with compiler engineers, fellow Applied Scientists, Hardware Architects and product teams to build the best ML-centric solutions for our devices - Publish in open source and present on Amazon's behalf at key ML conferences - NeurIPS, ICLR, MLSys.
US, CA, Culver City
MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Applied Scientist III Job Location: Culver City, California Job Number: AMZ10564141 Position 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, and run and analyze experiments in a production environment. Identify new opportunities for research in order to meet business goals. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. 40 hours / week, 8:00am-5:00pm, Salary Range: $167,100/year to $226,100/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000
IN, KA, Bengaluru
Have you ever wondered how that Amazon box with the smile arrives so quickly, where it came from, and how much it cost Amazon to deliver? The WW Amazon Logistics, Business Analytics team manages the delivery of tens of millions of products every week to Amazon's customers, achieving on-time delivery in a cost-effective manner. We are seeking an enthusiastic, customer-obsessed Research Science Manager(RSM) with strong analytical skills to join our team. This role is crucial in optimizing Amazon's vast delivery network and will have significant impact on the customer experience, particularly in the final phase of delivery. As a Research Science Manager, you will: 1. Address business challenges through building compelling cases and using data to influence change across the organization 2. Develop input and assumptions based on preexisting models to estimate costs and savings opportunities associated with varying levels of network growth and operations 3. Create metrics to measure business performance, identify root causes and trends, and prescribe action plans 4. Manage multiple high-impact projects simultaneously 5. Work with technology teams and product managers to develop new tools and systems supporting business growth 6. Communicate with and support various internal stakeholders and external audiences 7. Implement scheduling solutions, improve metrics, and develop scalable processes and tools Looking for minds with: Extensive experience in operations research and data-driven decision making Strong analytical and problem-solving skills Robust program management and research science skills Ability to work with a team and make independent decisions in ambiguous environments Customer-obsessed mindset with a focus on improving the Amazon delivery experience This role offers the autonomy to think strategically and make data-driven decisions from day one. Join us in shaping the future of e-commerce delivery and addressing the core challenges in our world-class operations space! Key job responsibilities Key job responsibilities 1. Advanced Modeling and Algorithm Development: Design and implement sophisticated machine learning models for logistics optimization Develop complex time series forecasting algorithms for demand prediction and resource allocation 2. AI and Machine Learning Integration: Architect and deploy AI-powered systems to enhance decision-making in logistics operations Implement deep learning techniques for image recognition in package sorting and handling Develop reinforcement learning algorithms for adaptive scheduling and resource management 3. Big Data Analytics and Processing: Design and implement distributed computing solutions for processing massive logistics datasets Utilize cloud computing platforms (e.g., AWS) for scalable data processing and analysis 4. AI-Driven Workflow Optimization: Design and implement AI agents for autonomous decision-making in logistics processes Create machine learning models for customer behavior analysis and personalized delivery options 5. Software Development and System Architecture: Write efficient, scalable code in languages such as Python, Java, or C++ Develop and maintain complex software systems for logistics optimization Stay at the forefront of AI and ML research Publish research findings in top-tier conferences and journals About the team We are Amazon's Last Mile Science and Analytics team, dedicated to improving e-commerce delivery. We work to optimize our vast network, forecast demand using machine learning, and enhance route efficiency. Our efforts focus on developing innovative delivery methods, applying AI to solve complex problems, and conducting geospatial analysis. We create simulations to refine processes and plan capacity effectively. Operating globally, we strive to develop adaptable solutions for diverse markets. We aim to advance logistics science, continually improving speed, efficiency, and customer satisfaction, in support of Amazon's mission to be Earth's most customer-centric company.
IN, KA, Bengaluru
Amazon Prime Video is looking for passionate, talented, and inventive Applied Scientists with a strong machine learning background to help build industry-leading Audio, Video and Language technology using GenAI. As part of the AI team in Amazon Prime Video, you will work on developing and fine-tuning LLMs and developing new large multimodal models to advance state-of-the-art in the translation, transcription and generation of multingual cinematic content. You will use the latest GenAI techniques to create and assess cinematic content like videos, audio, and captions, and more. You will design novel approaches to integrate speech, vision, and text for holistic understanding and generation of content, and Collaborate cross-functionally with product managers, engineers, and domain experts to define and deliver high-impact solutions. Your work will directly impact millions of our customers in the form of products and services that make use of speech and language technology on Prime Video content. Key job responsibilities We are looking to hire a top notch scientist with strong machine learning background, sharp research acumen and a hunger for solving ambiguous and challenging science problems. This person will work on developing and fine-tuning LLMs and developing new large multimodal models to advance state-of-the-art in the translation, transcription and generation of multingual cinematic content. They will be required to use the latest GenAI advancements to create and assess cinematic content like videos, audio, and captions, and more. Flavor of problems we are trying to solve: a) generating high quality subtitles in many languages meeting high customer satisfaction bar, b) developing foundation model capable of enabling many down stream tasks in localization and accessibility space, c) generating captions with plot pertinency, character identification etc. d) developing solution for assessing quality of subtitles, captions and metadata unified across different content types, linguistic vs non-linguistic aspects, different languages, and which mimics end user satisfaction while at the same time is explainable. About the team By 2027, Prime Video (PV) aspires to be the primary destination for customers to watch and the primary channel for partners to distribute premium cinematic content. The Content Reasoning, Enrichment & Localization (CoREL) science team’s mission is to develop AI to deeply understand the diverse facets of Prime Video's content across multiple languages, and to create content that power immersive, cinematic experiences. To drive this mission and delight our customers, the CoREL Science Bangalore team addresses the localization and accessibility aspects by a) understanding fine-grained information contained in content to enable generation of localized assets in different languages, b) generating subtitles and accessibility assets like captions across different content types and languages, c) assessing quality of generated (1P) and partner submitted (3P) assets and metadata to ensure defect free customer experience on PV.
US, CA, San Francisco
If you are interested in this position, please apply on Twitch's Career site https://www.twitch.tv/jobs/en/ About Us: Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day. We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X, and discover the projects we’re solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process. About the Role We are looking for an Applied Scientist to solve challenging and open-ended problems in the domain of Creators and content contextual signals. As an Applied Scientist on Twitch's GTM Science team, you will use applied machine learning to tackle ambiguous business problems across problem areas such as Ads, Brand Safety, Creator Sponsorship and Content Understanding. You will lead high profile projects where you will use a wide toolbox of ML tools to handle multiple types of data, including user behavior, metadata, and user generated content such as text and video. You will collaborate with a team of passionate scientists, engineers, and product stakeholders to develop these models, prototype and put them into production, where they can help Twitch's creators and viewers succeed and build communities. You will report to our Senior Data Science Manager for GTM. This position is located in San Francisco, CA. You Will - Build machine learning products to enrich Twitch’s content understanding and help creators and viewers build and discover their communities. - Propose, design, and oversee execution for high-impact projects that work backwards from customer problems to develop the right solution for the job. Know when to use a classical ML model versus a state-of-the-art one. - Collaborate with cross-functional engineering and product teams to prototype and deploy your models into flexible data pipelines and ML-based services. - Bring innovation and help drive science culture on the team by staying up to date and experimenting with new techniques in LLM, computer vision, inference and model evaluation. Perks * Medical, Dental, Vision & Disability Insurance * 401(k) * Maternity & Parental Leave * Flexible PTO * Amazon Employee Discount