Matt Grimes

Applied Scientist Manager, Marketplace Intelligence

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.

Applied Scientist, Machine Learning Accelerator - Annapurna Labs

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.

Economist II, PXT Central Science

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.

Applied Scientist, SSG Science

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.

Applied Scientist III - AMZ10564141

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

Applied Scientist

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

Applied Scientist, FinAuto

IN, KA, Bengaluru

Interested to build the next generation Financial systems that can handle billions of dollars in transactions? Interested to build highly scalable next generation systems that could utilize Amazon Cloud? Massive data volume + complex business rules in a highly distributed and service oriented architecture, a world class information collection and delivery challenge. Our challenge is to deliver the software systems which accurately capture, process, and report on the huge volume of financial transactions that are generated each day as millions of customers make purchases, as thousands of Vendors and Partners are paid, as inventory moves in and out of warehouses, as commissions are calculated, and as taxes are collected in hundreds of jurisdictions worldwide. Key job responsibilities • Understand the business and discover actionable insights from large volumes of data through application of machine learning, statistics or causal inference. • Analyse and extract relevant information from large amounts of Amazon’s historical transactions data to help automate and optimize key processes • Research, develop and implement novel machine learning and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection. • Use machine learning and analytical techniques to create scalable solutions for business problems. • Identify new areas where machine learning can be applied for solving business problems. • Partner with developers and business teams to put your models in production. • Mentor other scientists and engineers in the use of ML techniques. A day in the life • Understand the business and discover actionable insights from large volumes of data through application of machine learning, statistics or causal inference. • Analyse and extract relevant information from large amounts of Amazon’s historical transactions data to help automate and optimize key processes • Research, develop and implement novel machine learning and statistical approaches for anomaly, theft, fraud, abusive and wasteful transactions detection. • Use machine learning and analytical techniques to create scalable solutions for business problems. • Identify new areas where machine learning can be applied for solving business problems. • Partner with developers and business teams to put your models in production. • Mentor other scientists and engineers in the use of ML techniques. About the team The FinAuto TFAW(theft, fraud, abuse, waste) team is part of FGBS Org and focuses on building applications utilizing machine learning models to identify and prevent theft, fraud, abusive and wasteful(TFAW) financial transactions across Amazon. Our mission is to prevent every single TFAW transaction. As a Machine Learning Scientist in the team, you will be driving the TFAW Sciences roadmap, conduct research to develop state-of-the-art solutions through a combination of data mining, statistical and machine learning techniques, and coordinate with Engineering team to put these models into production. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards.

Principal Audio Scientist, Fauna

US, NY, New York

Fauna Robotics is building capable, safe, and delightful robots for everyday life, and voice is one of the most natural ways people will interact with them. Cloud speech and language models are good and getting better, but they can only work with the audio they receive, and a robot is a hard place to listen. Its microphones sit beside motors, fans, and moving joints. It speaks through its own loudspeaker while people talk over it. It moves, turns, and shares a room with several people at once. We are hiring a Principal Audio Scientist to be Fauna's technical authority on how our robots hear. You will design, prototype, and ship the hardest algorithms in the robot's audio system. You will set the audio architecture that other engineers build on, shape hardware decisions across robot generations, mentor the engineers and scientists working on audio, and be the person teams come to when the robot can't hear. Key job responsibilities - Set the long-range science roadmap and technical architecture for the robot's audio system, and serve as Fauna's primary technical authority on robot hearing - Design and implement suppression of the robot's own noise from motors, fans, and moving joints - Design and implement echo cancellation for the robot's own voice, so people can interrupt it naturally - Develop multi-microphone processing that holds up as the robot and the people around it move, including locating who is speaking so the robot can turn toward them - Make on-robot listening decisions robust to internal and external noise sources: wake word, voice activity, and whether speech is directed at the robot - Drive microphone and speaker placement, enclosure acoustics, and vibration isolation decisions with mechanical, electrical, and industrial design, backed by your own measurements - Design the robot-specific data collection and evaluation methods to validate the performance of our audio design - Present audio science and its tradeoffs to senior leadership and partner teams - Mentor scientists and engineers, raising the scientific bar for audio across the organization through design reviews, code reviews, and hiring

Robotics/AI Motor Control Scientist, Fauna

US, NY, New York

We are seeking a Robotics/AI Motor Control Scientist to develop cutting-edge machine learning algorithms for motor control systems in robots. In this role, you will focus on creating and optimizing intelligent motor control strategies to enable robots to perform complex, whole-body tasks. Your contributions will be essential in advancing robotics by enabling fluid, reliable, and safe interactions between robots and their environments. Key job responsibilities - Develop controllers that leverage reinforcement learning, imitation learning, or other advanced AI techniques to achieve natural, robust, and adaptive motor behaviors - Collaborate with multi-disciplinary teams to integrate motor control systems with robotic hardware, ensuring alignment with real-world constraints such as actuator dynamics and energy efficiency - Use simulation and real-world testing to refine and validate control algorithms - Stay updated on advancements in robotics, AI, and control systems to apply advanced techniques to robotic motion challenges - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers - Bridge research initiatives with practical engineering implementation About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you. an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.

Applied Scientist III, AGI Responsible AI (RAI)

US, CA, Sunnyvale

Amazon's Artificial General Intelligence (AGI) organization is seeking an Applied Scientist III to advance the science of Responsible AI evaluation for large language models and generative AI. In this role, you will lead the design and development of rigorous evaluation methods, benchmarks, and metrics that measure the safety, fairness, robustness, and trustworthiness of frontier models. You will work with large-scale datasets, modern deep learning frameworks, and world-class scientists and engineers to turn research into evaluation systems that shape model launch decisions at Amazon scale. Key job responsibilities - Lead the design and implementation of evaluation frameworks, benchmarks, and metrics for responsible AI, including safety, fairness, robustness, and harmful content. - Build scalable automated evaluation pipelines for large language models, including model-based and human-in-the-loop evaluation. - Partner with pretraining, post-training, and product teams to translate evaluation results into model improvements and launch decisions. - Conduct rigorous experimentation and statistical analysis, and publish research at top venues. - Mentor junior scientists and help raise the scientific bar of the team. - Champion responsible AI practices across the model development lifecycle. About the team The AGI Responsible AI (RAI) team builds the science and systems that make Amazon's large language models safe, fair, and trustworthy. We work on problems spanning safety evaluation, content moderation, watermarking, bias mitigation, and alignment. Our team values scientific rigor, customer obsession, and rapid iteration, and we collaborate closely with pretraining, post-training, and product teams across AGI.

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