Josh Miele, in a purple dress shirt, sits at a desk in an office, he is typing and looking at a computer screen, there are chairs and desks in the background
Josh Miele, an Amazon principal accessibility researcher, was selected a 2021 MacArthur Foundation Fellow. He has spent his career developing tools to make the world more accessible for people who are blind and visually impaired.
Meg Coyle / Amazon

Josh Miele: Amazon’s resident MacArthur Fellow

Miele has merged a lifelong passion for science with a mission to make the world more accessible for people with disabilities.

In September 2021, when Josh Miele, an Amazon principal accessibility researcher, got a text from someone at the MacArthur Foundation requesting a phone call, his heart leapt. For anyone in the arts and sciences, a MacArthur Fellowship, known as the “genius” grant, is akin to winning the lottery. You can’t apply for the $625,000 fellowship; it just arrives, mysteriously, out of the ether with a phone call from the foundation.

For Miele, who is blind and has spent his career developing tools to make the world more accessible for people who are blind and visually impaired, a MacArthur grant had long been a fantastical dream.

Joshua Miele, Adaptive Technology Designer | 2021 MacArthur Fellow

“Everybody has things that they imagine might happen to them,” Miele said. “And some things are more realistic than others. You think, ‘Wouldn’t it be nice to get married, have kids, get a great job at Amazon, and, yes, wouldn’t it be nice to get a MacArthur grant?’ Some dreams you can work on and make happen yourself, and some you have to wait and hope for. I won’t deny that one of my long-time fantasies was that I would get a MacArthur Fellowship.”

Assuming the call was to ask his opinion about a possible recipient, he was ecstatic to learn he was among the 25 2021 fellows selected by the foundation. The five-year grant provides money that recipients can use however they want. For someone like Miele, who spent years in a non-profit accessibility thinktank in an endless quest for grant money, the MacArthur news left him with sweaty palms, ringing ears, and pure joy.

“It was extraordinary,” he declared.

A devotion to accessibility

Yet given his life’s work, the grant was a surprise to no one who knows Miele. After graduating from the University of California, Berkeley with a PhD in psychoacoustics in 2003, Miele worked for 16 years at the non-profit Smith-Kettlewell Eye Research Institute in San Francisco as a principal scientist and researcher. He devoted his life to fostering accessibility for the blind and visually impaired.

Josh using a refreshable braille display in his home office.jpg
Josh Miele using a refreshable braille display in his home office in Berkeley, California.
Stephen Lam/Amazon

He began working with Amazon Lab126, which designs and engineers Amazon devices and services, in 2019. There Miele joined the group of designers and developers who built the Echo family of devices, Kindle, Fire tablets, Fire TV, Amazon Basics Microwaves, and a growing list of innovative products.

His work is with the accessibility team that seeks to make Amazon products intuitively useful for individuals with disabilities.

Related content
Alexa Fund company unlocks voice-based computing for people who have trouble using their voices.

His aim is to ensure that the designers, product managers, and team members have as clear an understanding as possible of the user experience for customers with disabilities.

“What I’m doing is making sure that the folks who are doing the design understand the customers they are designing for,” Miele explained. “That’s a special and important part of the puzzle because some people doing the work don’t have disabilities themselves and don’t innately have the deep understanding of what the customer requirements are.”

Improving Show and Tell

For example, when Miele joined Lab126, the group was working on Show and Tell, an Alexa feature for Echo Show devices that uses the camera and voice interface to help people who are blind identify products. Employing advanced computer vision and machine learning models for object recognition, Show and Tell can be a vital tool in the kitchen of a customer who is blind or has low vision. A person holds up an object and asks, “Alexa, what am I holding?” and gets an immediate answer.

New Amazon Echo Feature Increases Accessibility (With Audio Description) | Amazon News

The project was stymied, however, by the developers’ struggle to match each product perfectly. If they didn’t get a 100-percent match, the team felt they had failed.

Miele helped the team understand that they needed only to provide useful context, even just a word or two, for a person who is blind or visually impaired to identify the product. The team focused on kitchen and pantry items — things that come in cans, boxes, bottles, and tubes. The goal: Recognize items in Amazon’s vast product catalogue, or if that wasn’t possible, recognize brands and logos that could give the customer enough information to know what they held in their hand.

“If I touch a can of something, I know it’s a can,” Miele explained, “but I don’t know if it’s a can of black beans or pineapple. So, if I’m making chili, and I open a can of pineapple, I’m going to be pretty irritated.”

Related content
Gari Clifford, the chair of the Department of Biomedical Informatics at Emory University and an Amazon Research Award recipient, wants to transform healthcare.

“I helped design an interaction model that would look for an exact match,” he added, “but if Alexa didn’t get that, it would look for brand recognition. Alexa would look for logos or text that would offer at least some clue as to what was in the can.”

The team created what he called “a gentle letdown curve.” If Alexa can’t find the exact information, Alexa politely apologizes — but doesn’t give up. “I don’t know what it is, but I saw the words `whole black beans’ on the label,” Alexa says. It isn’t an exact match, Miele noted, at least you know what is in the can, which is still incredibly helpful.

Additionally, Miele worked with the team to create audio feedback where Alexa guides the customer to hold the object in the camera’s field of view. Without that, Alexa might be unable to identify the product and frustration could set in.

“Doing things the right way”

Miele also has provided important input into the team’s braille display support and Braille Screen Input technology.

“The most important thing I do is work with my colleagues to test these experiences with real blind and visually impaired customers,” Miele said. “Usability testing is a fairly well known art, but when you’re testing with specialized populations, like people who are blind or deaf, or people using wheelchairs, there are certain adjustments that you want to make to your research protocol so that you are doing things the right way.”

Related content
Participating teams reported their progress at a workshop earlier this month.

For example, Miele helped the design team understand that it was important that things like consent forms be made accessible.

“Designing research protocols so that people with disabilities are comfortable and properly accommodated is a really important part of research,” Miele said. “The very best way to ensure that the thing you’re designing works for the people you are designing it for is to have people on the team who are going to be customers for that experience.”

A remarkable journey

Miele’s story is a remarkable one, but he discourages others from focusing too much on what happened to him as a child, and instead to consider who he is and what he’s accomplished. He was blinded at age 4 when an assailant in his Brooklyn, New York neighborhood poured sulfuric acid over his head, which blinded and disfigured him.

Josh Miele is seen wearing a suit, sitting in a chair while playing a bass guitar, there is a mic stand and an amp in the foreground
Josh Miele plays bass guitar and has developed a new braille code for writing jazz chord charts.
Barbara Butkus

With the support of incredible parents, teachers and colleagues, he has never thought of himself as being less capable.

He has a full and accomplished life. Miele is married and has two teenage children. He plays the bass guitar and has developed a new braille code for writing jazz chord charts. He is a serious cook and woodworker and loves to hike. He is a proud member of the disability community.

He doesn’t focus on what happened to him because for him, it was simply the challenge life handed him.

“It wasn’t a choice I made,” he said about his positive outlook. “It never even occurred to me to feel sorry for myself. I just wanted to go through life and do the things I was interested in.”

An important epiphany

Miele’s love of science emerged early. He wanted to build rockets, become a space scientist, and explore outer space. Shortly after beginning an undergraduate physics degree at UC Berkeley, he interned with NASA, where he worked in planetary science. It wasn’t until later when he took a job at a software startup named Berkeley Systems, where he worked on some of the first graphical user interface (GUI) screen readers for the blind and visually impaired. That produced an epiphany.

“I realized that the work I was doing in accessibility was both rewarding to me and something that not many people could do at the level I was able to do it,” he recalled. “I thought, ‘There are plenty of people who could be great planetary scientists but there were not a lot of people who could design cool stuff for blind people and meet the needs of the people who were going to use it.’”

Josh Miele, standing, gives advice to a student who is seated during a soldering workshop. Several students are sitting at a large table with soldering equipment.
Josh Miele, seen here leading a soldering workshop, says, “I am blind and that is my superpower in this. I’ve been working in accessibility for a really long time and not just for people who are blind and visually impaired, but for people with all kinds of disabilities."
Jean Miele

His colleague at Berkeley Systems, Peter Korn, was recruited to join the Amazon Lab126 accessibility team in 2013. One of his first moves was to create an external advisory council of disability experts and he asked Miele to join the council. Korn offered council members a peek behind the curtain at some of the lab’s projects. After one of those sessions, Miele took Korn aside and said, “You know, I’d really love to play a bigger role in helping bring some of those technologies you’re talking about to life.”

Korn responded, “Well, I would love to have you.”

Korn, who has been a colleague and friend for 30 years, was among those who were not surprised at Miele’s MacArthur grant.

“I’ve been incredibly impressed by his creativity, his design sense, his energy and passion, and his inventiveness,” Korn said. “He has a really good sense of what somebody who doesn’t understand technology faces.”

“My superpower”

“I am blind and that is my superpower in this,” Miele said. “I’ve been working in accessibility for a really long time and not just for people who are blind and visually impaired, but for people with all kinds of disabilities. I not only have a fairly good understanding of what some of the basic requirements are for a wide range of disabilities, but I also know how to connect with those communities and bring their voices into the conversation with the designers, developers, and product managers.”

I love accessibility. There’s a social justice aspect to it. You’re working on inclusion and accessibility of information.
Josh Miele

After many years in the non-profit sector, Miele is happy with his move to the technology industry.

“I love what I do,” he declared. “I love accessibility. There’s a social justice aspect to it. You’re working on inclusion and accessibility of information. You’re empowering people to do the things they want to do, which is extremely exciting for me. I’m strongly motivated to build cool things for blind people. I want blind people’s lives to be better. I also really like challenges, finding new, fun exciting things to work on and at Amazon, there is absolutely no shortage of cool, interesting, thought-provoking design challenges for accessibility.”

To learn more about Amazon Accessibility, please visit amazon.com/accessibility.

Related content

US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for healthcare. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Design and implement novel AI/ML solutions for complex healthcare challenges • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • Navigate ambiguity and create clarity in early-stage product development • Collaborate with cross-functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions • Establish best practices for ML experimentation, evaluation, development and deployment • Partner with leadership to define roadmap and strategic initiatives You’ll need a strong background in AI/ML, proven leadership skills, and the ability to translate complex concepts into actionable plans. You’ll also need to effectively translate research findings into practical solutions. A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
CA, BC, Vancouver
Have you ever wondered how Amazon predicts delivery times and ensures your orders arrive exactly when promised? Have you wondered where all those Amazon semi-trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? Does the idea of having worldwide impact on Amazon's multimodal logistics network that includes planes, trucks, and vans sound exciting to you? Are you interested in developing Generative AI solutions using state-of-the-art LLM techniques to revolutionize how Amazon optimizes the fulfillment of millions of customer orders globally with unprecedented scale and precision? If so, then we want to talk with you! Join our team to apply the latest advancements in Generative AI to enhance our capability and speed of decision making. Fulfillment Planning & Execution (FPX) Science team within SCOT- Fulfillment Optimization owns and operates optimization, machine learning, and simulation systems that continually optimize the fulfillment of millions of products across Amazon’s network in the most cost-effective manner, utilizing large scale optimization, advanced machine learning techniques, big data technologies, and scalable distributed software on the cloud that automates and optimizes inventory and shipments to customers under the uncertainty of demand, pricing, and supply. The team has embarked on its Generative AI to build the next-generation AI agents and LLM frameworks to promote efficiency and improve productivity. We’re looking for a passionate, results-oriented, and inventive machine learning scientist who can design, build, and improve models for our outbound transportation planning systems. You will work closely with our product managers and software engineers to disambiguate complex supply chain problems and create ML / AI solutions to solve those problems at scale. You will work independently in an ambiguous environment while collaborating with cross-functional teams to drive forward innovation in the Generative AI space. Key job responsibilities * Design, develop, and evaluate tailored ML/AI, models for solving complex business problems. * Research and apply the latest ML / AI techniques and best practices from both academia and industry. * Identify and implement novel Generative AI use cases to deliver value. * Design and implement Generative AI and LLM solutions to accelerate development and provide intuitive explainability of complex science models. * Develop and implement frameworks for evaluation, validation, and benchmarking AI agents and LLM frameworks. * Think about customers and how to improve the customer delivery experience. * Use analytical techniques to create scalable solutions for business problems. * Work closely with software engineering teams to build model implementations and integrate successful models and algorithms in production systems at large scale. * Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. A day in the life You will have the opportunity to learn how Amazon plans for and executes within its logistics ne twork including Fulfillment Centers, Sort Centers, and Delivery Stations. In this role, you will design and develop Machine Learning / AI models with significant scope, impact, and high visibility. You will focus on designing, developing, and deploying Generative AI solutions at scale that will improve efficiency, increase productivity, accelerate development, automate manual tasks, and deliver value to our internal customers. Your solutions will impact business segments worth many-billions-of-dollars and geographies spanning multiple countries and markets. From day one, you will be working with bar raising scientists, engineers, and designers. You will also collaborate with the broader science community in Amazon to broaden the horizon of your work. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career. About the team FPX Science tackles some of the most mathematically complex challenges in transportation planning and execution space to improve Amazon's operational efficiency worldwide at a scale that is unique to Amazon. We own the long-term and intermediate-term planning of Amazon’s global fulfillment centers and transportation network as well as the short-term network planning and execution that determines the optimal flow of customer orders through Amazon fulfillment network. FPX science team is a group of scientists with different technical backgrounds including Machine Learning and Operations Research, who will collaborate closely with you on your projects. Our team directly supports multiple functional areas across SCOT - Fulfillment Optimization and the research needs of the corresponding product and engineering teams. We disambiguate complex supply chain problems and create innovative data-driven solutions to solve those problems at scale with a mix of science-based techniques including Operations Research, Simulation, Machine Learning, and AI to tackle some of our biggest technical challenges. In addition, we are incorporating the latest advances in Generative AI and LLM techniques in how we design, develop, enhance, and interpret the results of these science models.
US, WA, Bellevue
Amazon LEO is Amazon’s low Earth orbit satellite network. Our mission is to deliver fast, reliable internet connectivity to customers beyond the reach of existing networks. From individual households to schools, hospitals, businesses, and government agencies, Amazon Leo will serve people and organizations operating in locations without reliable connectivity. The Amazon LEO Infrastructure Data Engineering, Analytics, and Science team owns designing, implementing, and operating systems/models that support the optimal demand/capacity planning function. We are looking for a talented scientist to implement LEO's long-term vision and strategy for capacity simulations and network bandwidth optimization. This effort will be instrumental in helping LEO execute on its business plans globally. As one of our valued team members, you will be obsessed with matching our standards for operational excellence with a relentless focus on delivering results. Key job responsibilities In this role, you will: Work cross-functionally with product, business development, and various technical teams (engineering, science, R&D, simulations, etc.) to implement the long-term vision, strategy, and architecture for capacity simulations and inventory optimization. Design and deliver modern, flexible, scalable solutions to complex optimization problems for operating and planning satellite resources. Contribute to short and long terms technical roadmap definition efforts to predict future inventory availability and key operational and financial metrics across the network. Design and deliver systems that can keep up with the rapid pace of optimization improvements and simulating how they interact with each other. Analyze large amounts of satellite and business data to identify simulation and optimization opportunities. Synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication to drive change across LEO. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
US, CA, San Francisco
Amazon has launched a new research lab in San Francisco to develop foundational capabilities for useful AI agents. We’re enabling practical AI to make our customers more productive, empowered, and fulfilled. In particular, our work combines large language models (LLMs) with reinforcement learning (RL) to solve reasoning, planning, and world modeling in both virtual and physical environments. Our research builds on that of Amazon’s broader AGI organization, which recently introduced Amazon Nova, a new generation of state-of-the-art foundation models (FMs). Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where agents can redefine what AI makes possible. We’d love for you to join our lab and build it from the ground up! Key job responsibilities You will contribute directly to AI agent development in an applied research role, including model training, dataset design, and pre- and post-training optimization. You will be hired as a Member of Technical Staff.
US, MA, Boston
AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. That is why Amazon is investing in generative AI (GenAI) and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us. We are looking for a Research Scientist with strong technical skills which includes coding and natural language processing experience in dataset construction, training and evaluating models, and automatic processing of large datasets. You will play a critical role in driving innovation and advancing the state-of-the-art in natural language processing and machine learning. You will work closely with cross-functional teams, including product managers, language engineers, and other scientists. Key job responsibilities Specifically, the Research Scientist will: • Ensure quality of speech/language/other data throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc. • Clean, analyze and select speech/language/other data to achieve goals • Build and test models that elevate the customer experience • Collaborate with colleagues from science, engineering and business backgrounds • Present proposals and results in a clear manner backed by data and coupled with actionable conclusions • Work with engineers to develop efficient data querying infrastructure for both offline and online use cases
US, MA, Boston
AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. That is why Amazon is investing in generative AI (GenAI) and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us. We are looking for a Research Scientist with strong technical skills which includes coding and natural language processing experience in dataset construction, training and evaluating models, and automatic processing of large datasets. You will play a critical role in driving innovation and advancing the state-of-the-art in natural language processing and machine learning. You will work closely with cross-functional teams, including product managers, language engineers, and other scientists. Key job responsibilities Specifically, the Research Scientist will: • Ensure quality of speech/language/other data throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc. • Clean, analyze and select speech/language/other data to achieve goals • Build and test models that elevate the customer experience • Collaborate with colleagues from science, engineering and business backgrounds • Present proposals and results in a clear manner backed by data and coupled with actionable conclusions • Work with engineers to develop efficient data querying infrastructure for both offline and online use cases
US, WA, Bellevue
This is currently a 12 month temporary contract opportunity with the possibility to extend to 24 months based on business needs. The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services. A day in the life An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.
CA, ON, Toronto
The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-the-art 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 Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack—from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences—all designed to deliver meaningful value. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we’re helping businesses grow on Amazon.com and beyond! Key job responsibilities This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to: - Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences. - Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life. - Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization. - Contribute to the enhancement of team’s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. - Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team. A day in the life As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced—elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon’s rich data and the world’s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science. About the team The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack—from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences—all designed to deliver meaningful value. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we’re helping businesses grow on Amazon.com and beyond!
US, MA, N.reading
Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon Industrial Robotics we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of dexterous manipulation system that: - Enables unprecedented generalization across diverse tasks - Enables contact-rich manipulation in different environments - Seamlessly integrates low-level skills and high-level behaviors - Leverage mechanical intelligence, multi-modal sensor feedback and advanced control techniques. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities - Design and implement methods for dexterous manipulation - Design and implement methods for use of dexterous end effectors with force and tactile sensing - Develop a hierarchical system that combines low-level control with high-level planning - Utilize state-of-the-art manipulation models and optimal control techniques
US, WA, Bellevue
This is currently a 12 month temporary contract opportunity with the possibility to extend to 24 months based on business needs. The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services. A day in the life An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.