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

IN, TS, Hyderabad
Welcome to the Worldwide Returns & ReCommerce team (WWR&R) at Amazon.com. WWR&R is an agile, innovative organization dedicated to ‘making zero happen’ to benefit our customers, our company, and the environment. Our goal is to achieve the three zeroes: zero cost of returns, zero waste, and zero defects. We do this by developing products and driving truly innovative operational excellence to help customers keep what they buy, recover returned and damaged product value, keep thousands of tons of waste from landfills, and create the best customer returns experience in the world. We have an eye to the future – we create long-term value at Amazon by focusing not just on the bottom line, but on the planet. We are building the most sustainable re-use channel we can by driving multiple aspects of the Circular Economy for Amazon – Returns & ReCommerce. Amazon WWR&R is comprised of business, product, operational, program, software engineering and data teams that manage the life of a returned or damaged product from a customer to the warehouse and on to its next best use. Our work is broad and deep: we train machine learning models to automate routing and find signals to optimize re-use; we invent new channels to give products a second life; we develop highly respected product support to help customers love what they buy; we pilot smarter product evaluations; we work from the customer backward to find ways to make the return experience remarkably delightful and easy; and we do it all while scrutinizing our business with laser focus. You will help create everything from customer-facing and vendor-facing websites to the internal software and tools behind the reverse-logistics process. You can develop scalable, high-availability solutions to solve complex and broad business problems. We are a group that has fun at work while driving incredible customer, business, and environmental impact. We are backed by a strong leadership group dedicated to operational excellence that empowers a reasonable work-life balance. As an established, experienced team, we offer the scope and support needed for substantial career growth. Amazon is earth’s most customer-centric company and through WWR&R, the earth is our customer too. Come join us and innovate with the Amazon Worldwide Returns & ReCommerce team!
GB, MLN, Edinburgh
We’re looking for a Machine Learning Scientist in the Personalization team for our Edinburgh office experienced in generative AI and large models. You will be responsible for developing and disseminating customer-facing personalized recommendation models. This is a hands-on role with global impact working with a team of world-class engineers and scientists across the Edinburgh offices and wider organization. You will lead the design of machine learning models that scale to very large quantities of data, and serve high-scale low-latency recommendations to all customers worldwide. You will embody scientific rigor, designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will work alongside a science team to delight customers by aiding in recommendations relevancy, and raise the profile of Amazon as a global leader in machine learning and personalization. Successful candidates will have strong technical ability, focus on customers by applying a customer-first approach, excellent teamwork and communication skills, and a motivation to achieve results in a fast-paced environment. Our position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. If you are selected, you have the opportunity to make a difference to our business by designing and building state of the art machine learning systems on big data, leveraging Amazon’s vast computing resources (AWS), working on exciting and challenging projects, and delivering meaningful results to customers world-wide. Key job responsibilities Develop machine learning algorithms for high-scale recommendations problems. Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgement. Collaborate with software engineers to integrate successful experimental results into large-scale, highly complex Amazon production systems capable of handling 100,000s of transactions per second at low latency. Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment.
US, WA, Seattle
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! In Prime Video READI, our mission is to automate infrastructure scaling and operational readiness. We are growing a team specialized in time series modeling, forecasting, and release safety. This team will invent and develop algorithms for forecasting multi-dimensional related time series. The team will develop forecasts on key business dimensions with optimization recommendations related to performance and efficiency opportunities across our global software environment. As a founding member of the core team, you will apply your deep coding, modeling and statistical knowledge to concrete problems that have broad cross-organizational, global, and technology impact. Your work will focus on retrieving, cleansing and preparing large scale datasets, training and evaluating models and deploying them to production where we continuously monitor and evaluate. You will work on large engineering efforts that solve significantly complex problems facing global customers. You will be trusted to operate with complete independence and are often assigned to focus on areas where the business and/or architectural strategy has not yet been defined. You must be equally comfortable digging in to business requirements as you are drilling into design with development teams and developing production ready learning models. You consistently bring strong, data-driven business and technical judgment to decisions. You will work with internal and external stakeholders, cross-functional partners, and end-users around the world at all levels. Our team makes a big impact because nothing is more important to us than delivering for our customers, continually earning their trust, and thinking long term. You are empowered to bring new technologies to your solutions. If you crave a sense of ownership, this is the place to be.
US, WA, Seattle
Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. The Ad Response Prediction team in Sponsored Products organization build advanced deep-learning models, large-scale machine-learning pipelines, and real-time serving infra to match shoppers’ intent to relevant ads on all devices, for all contexts and in all marketplaces. Through precise estimation of shoppers’ interaction with ads and their long-term value, we aim to drive optimal ads allocation and pricing, and help to deliver a relevant, engaging and delightful ads experience to Amazon shoppers. As the business and the complexity of various new initiatives we take continues to grow, we are looking for talented Applied Scientists to join the team. Key job responsibilities As a Applied Scientist II, you will: * Conduct hands-on data analysis, build large-scale machine-learning models and pipelines * Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production * Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior management * Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving * Provide technical leadership, research new machine learning approaches to drive continued scientific innovation * Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences
US, WA, Seattle
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities As an Applied Scientist in the Content Understanding Team, you will lead the end-to-end research and deployment of video and multi-modal models applied to a variety of downstream applications. More specifically, you will: - Work backwards from customer problems to research and design scientific approaches for solving them - Work closely with other scientists, engineers and product managers to expand the depth of our product insights with data, create a variety of experiments to determine the high impact projects to include in planning roadmaps - Stay up-to-date with advancements and the latest modeling techniques in the field - Publish your research findings in top conferences and journals About the team Our Prime Video Content Understanding team builds holistic media representations (e.g. descriptions of scenes, semantic embeddings) and apply them to new customer experiences supply chain problems. Our technology spans the entire Prime Video catalogue globally, and we enable instant recaps, skip intro timing, ad placement, search, and content moderation.
IN, HR, Gurugram
We're on a journey to build something new a green field project! Come join our team and build new discovery and shopping products that connect customers with their vehicle of choice. We're looking for a talented Senior Applied Scientist to join our team of product managers, designers, and engineers to design, and build innovative automotive-shopping experiences for our customers. This is a great opportunity for an experienced engineer to design and implement the technology for a new Amazon business. We are looking for a Applied Scientist to design, implement and deliver end-to-end solutions. We are seeking passionate, hands-on, experienced and seasoned Senior Applied Scientist who will be deep in code and algorithms; who are technically strong in building scalable computer vision machine learning systems across item understanding, pose estimation, class imbalanced classifiers, identification and segmentation.. You will drive ideas to products using paradigms such as deep learning, semi supervised learning and dynamic learning. As a Senior Applied Scientist, you will also help lead and mentor our team of applied scientists and engineers. You will take on complex customer problems, distill customer requirements, and then deliver solutions that either leverage existing academic and industrial research or utilize your own out-of-the-box but pragmatic thinking. In addition to coming up with novel solutions and prototypes, you will directly contribute to implementation while you lead. A successful candidate has excellent technical depth, scientific vision, project management skills, great communication skills, and a drive to achieve results in a unified team environment. You should enjoy the process of solving real-world problems that, quite frankly, haven’t been solved at scale anywhere before. Along the way, we guarantee you’ll get opportunities to be a bold disruptor, prolific innovator, and a reputed problem solver—someone who truly enables AI and robotics to significantly impact the lives of millions of consumers. Key job responsibilities Architect, design, and implement Machine Learning models for vision systems on robotic platforms Optimize, deploy, and support at scale ML models on the edge. Influence the team's strategy and contribute to long-term vision and roadmap. Work with stakeholders across , science, and operations teams to iterate on design and implementation. Maintain high standards by participating in reviews, designing for fault tolerance and operational excellence, and creating mechanisms for continuous improvement. Prototype and test concepts or features, both through simulation and emulators and with live robotic equipment Work directly with customers and partners to test prototypes and incorporate feedback Mentor other engineer team members. A day in the life - 6+ years of building machine learning models for retail application experience - PhD, or Master's degree and 6+ years of applied research experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning - Demonstrated expertise in computer vision and machine learning techniques.
US, WA, Seattle
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities As an Applied Scientist in the Content Understanding Team, you will lead the end-to-end research and deployment of video and multi-modal models applied to a variety of downstream applications. More specifically, you will: - Work backwards from customer problems to research and design scientific approaches for solving them - Work closely with other scientists, engineers and product managers to expand the depth of our product insights with data, create a variety of experiments to determine the high impact projects to include in planning roadmaps - Stay up-to-date with advancements and the latest modeling techniques in the field - Publish your research findings in top conferences and journals About the team Our Prime Video Content Understanding team builds holistic media representations (e.g. descriptions of scenes, semantic embeddings) and apply them to new customer experiences supply chain problems. Our technology spans the entire Prime Video catalogue globally, and we enable instant recaps, skip intro timing, ad placement, search, and content moderation.
US, WA, Seattle
Do you want to re-invent how millions of people consume video content on their TVs, Tablets and Alexa? We are building a free to watch streaming service called Fire TV Channels (https://techcrunch.com/2023/08/21/amazon-launches-fire-tv-channels-app-400-fast-channels/). Our goal is to provide customers with a delightful and personalized experience for consuming content across News, Sports, Cooking, Gaming, Entertainment, Lifestyle and more. You will work closely with engineering and product stakeholders to realize our ambitious product vision. You will get to work with Generative AI and other state of the art technologies to help build personalization and recommendation solutions from the ground up. You will be in the driver's seat to present customers with content they will love. Using Amazon’s large-scale computing resources, you will ask research questions about customer behavior, build state-of-the-art models to generate recommendations and run these models to enhance the customer experience. You will participate in the Amazon ML community and mentor Applied Scientists and Software Engineers with a strong interest in and knowledge of ML. Your work will directly benefit customers and you will measure the impact using scientific tools.
US, MA, Boston
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to build industry-leading technology with Large Language Models (LLMs) and multi-modal systems. You will support projects that work on technologies including multi-modal model alignment, moderation systems and evaluation. Key job responsibilities As an Applied Scientist with the AGI team, you will support the development of novel algorithms and modeling techniques, to advance the state of the art with LLMs. 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 generative artificial intelligence (GenAI). You are also expected to publish in top tier conferences. About the team The AGI team has a mission to push the envelope in LLMs and multimodal systems. Specifically, we focus on model alignment with an aim to maintain safety while not denting utility, in order to provide the best-possible experience for our customers.
IN, HR, Gurugram
Our customers have immense faith in our ability to deliver packages timely and as expected. A well planned network seamlessly scales to handle millions of package movements a day. It has monitoring mechanisms that detect failures before they even happen (such as predicting network congestion, operations breakdown), and perform proactive corrective actions. When failures do happen, it has inbuilt redundancies to mitigate impact (such as determine other routes or service providers that can handle the extra load), and avoids relying on single points of failure (service provider, node, or arc). Finally, it is cost optimal, so that customers can be passed the benefit from an efficiently set up network. Amazon Shipping is hiring Applied Scientists to help improve our ability to plan and execute package movements. As an Applied Scientist in Amazon Shipping, you will work on multiple challenging machine learning problems spread across a wide spectrum of business problems. You will build ML models to help our transportation cost auditing platforms effectively audit off-manifest (discrepancies between planned and actual shipping cost). You will build models to improve the quality of financial and planning data by accurately predicting ship cost at a package level. Your models will help forecast the packages required to be pick from shipper warehouses to reduce First Mile shipping cost. Using signals from within the transportation network (such as network load, and velocity of movements derived from package scan events) and outside (such as weather signals), you will build models that predict delivery delay for every package. These models will help improve buyer experience by triggering early corrective actions, and generating proactive customer notifications. Your role will require you to demonstrate Think Big and Invent and Simplify, by refining and translating Transportation domain-related business problems into one or more Machine Learning problems. You will use techniques from a wide array of machine learning paradigms, such as supervised, unsupervised, semi-supervised and reinforcement learning. Your model choices will include, but not be limited to, linear/logistic models, tree based models, deep learning models, ensemble models, and Q-learning models. You will use techniques such as LIME and SHAP to make your models interpretable for your customers. You will employ a family of reusable modelling solutions to ensure that your ML solution scales across multiple regions (such as North America, Europe, Asia) and package movement types (such as small parcel movements and truck movements). You will partner with Applied Scientists and Research Scientists from other teams in US and India working on related business domains. Your models are expected to be of production quality, and will be directly used in production services. You will work as part of a diverse data science and engineering team comprising of other Applied Scientists, Software Development Engineers and Business Intelligence Engineers. You will participate in the Amazon ML community by authoring scientific papers and submitting them to Machine Learning conferences. You will mentor Applied Scientists and Software Development Engineers having a strong interest in ML. You will also be called upon to provide ML consultation outside your team for other problem statements. If you are excited by this charter, come join us!