De'Aira Bryant, who has done two internships at Amazon, and is a fourth-year computer science PhD student at the Georgia Institute of Technology, is seen posing in front of a wall with some transportation logos and Amazon Web Services written on it
De'Aira Bryant, who has done two internships at Amazon, is a fourth-year computer science PhD student at the Georgia Institute of Technology, where her research focuses on the application of robotics in health care and rehabilitation.
Courtesy of De'Aira Bryant

How De’Aira Bryant found her path into robotics

The computer scientist recently finished her second internship at Amazon, where she worked on a new way to estimate the human expression on faces in images.

Growing up in Estill, South Carolina, De’Aira Bryant didn’t know she was interested in computer science until she was persuaded to explore the field by her mother, who noted that computer scientists have good career prospects and get to do interesting work.

“I was handy with making flyers and doing the programs for church, that type of thing,” Bryant says. “She somehow convinced me that was computer science and I had no way to know better.”

In her first class as a computer science major at the University of South Carolina (UofSC), she realized that she didn’t really know what computer science entailed. “I was completely out of my league, coming from a small town with no computer science or robotics background at all.”

De'Aira Bryant is seen standing on a stage with a screen elevated above her in the background showing robots at her TEDx Talk
At her TEDx talk, De'Aira Bryant discussed how lessons from society's technological past can shed light on embracing a future with social robots.
Courtesy of De'Aira Bryant

Bryant immediately wanted to change her major, but Karina Liles — the graduate teaching assistant and the only female TA in the program at that time — convinced her to stay. “We were doing that ‘Hello, World!’ program and I was like: Do you want me to type it on Word? What do you mean, I'm writing a program?” Bryant remembers Liles looked at her in astonishment and set out to help her.

After the initial shock, Bryant started to thrive.

“It actually worked out for me, because I've always been really good at math, I also got a minor in math. And later I realized that what I actually like is logic, which was perfect for a computer science student at UofSC, because a lot of courses focused on the principles of logic.”

It turned out her mother was right after all.

Today, she’s a fourth-year computer science PhD student at the Georgia Institute of Technology, where her research focuses on the application of robotics in health care and rehabilitation. Over the years, Bryant has received research awards, given a TEDx Talk, and even programmed a robot that starred in a movie. Having recently completed her second internship at Amazon Web Services (AWS), she still finds time to think about fun and exciting ways to make computer science more accessible to diverse populations.

Making robots dance (and act)

Right after her first class, Bryant was invited by Liles, the TA, to do an internship at Assistive Robotics and Technology Lab (ART lab), headed by Jenay Beer, who was Liles’ advisor at the time and also played a crucial role in Bryant’s education at UofSC. (Currently, Liles is a professor at Claflin University and Beer is a professor at the University of Georgia.) Bryant didn’t think twice before accepting.

“I have my own desk, and I’m getting paid? Sign me up! What better job could there be?” she remembers thinking. She worked on designing systems for children in schools that did not have computer science curriculums, using robots as a method of engagement and exposure.

Initially, she would prepare the robots for studies, take them in the field, and watch kids interact with them. Later, she got to take crash courses to learn how to program them. “I don't think I was interested in robotics until I got to see to see how they were used, their application in the real world,” she says. The fact that she loved seeing them in action made her want to learn how to make them work.

As an undergrad, she started to program these robots to do short dance moves. She posted those clips to her social media, which piqued the curiosity of kids who followed her.

An unexpected journey: De'Aira Bryant

“I thought, ‘I'm going to trick them into asking more questions and I'm going to recruit more computer scientists by posting robots dancing,’” she says. “That kind of turned into a thing. Now I have a whole social media presence on making robots dance and do cool stuff.”

Bryant is deeply interested in changing the way computer science is taught.

From a culturally relevant perspective, a lot of the ways that we teach these concepts can miss the mark with a lot of students, especially students who come from minority backgrounds.
De'Aira Bryant

“From a culturally relevant perspective, a lot of the ways that we teach these concepts can miss the mark with a lot of students, especially students who come from minority backgrounds.” She says that throughout her computer science curriculum, a lot of the examples and problems proposed by the professors were not relevant to her. “I would completely rewrite the problem and that was how I was able to make it through my undergrad and graduate education.”

Currently, her main research at the Georgia Institute of Technology is focused on the applications of robotics on rehabilitation for children who have motor and cognitive disabilities.

“That kind of attracted me and now we have more robots and more resources and we’re linked with rehabilitative therapy centers in Atlanta and getting to work in those places as well,” she said.

Bryant still uses the expertise she acquired with the dancing robots. When HBO Max was filming the movie Superintelligence on Georgia Tech’s campus in 2019 and wanted to add cool futuristic robot scenes, Bryant’s adviser, Ayanna Howard, who today is dean and professor in the College of Engineering at Ohio State University, said she would be the right person for the job.

She had two weeks to prepare.

By the time she got to the set, the script had changed and she ended up having to redo the work on the set. “I was programming in real-time. And I think the movie people were so excited about that. They were standing over my shoulders saying, 'You’re actually coding.'” Bryant got to meet Melissa McCarthy, the star of the movie, and teach her kids how to make the robot move. “They all wanted pictures with the robot. I felt like my robot was the biggest star on the set.”

Interning at Amazon

Bryant then met Nashlie Sephus, a machine learning technology evangelist for AWS, at the National GEM Consortium Fellowship conference in 2019 (Bryant is a current GEM fellow and Sephus is an alum). After Bryant presented her research during a competition, Sephus approached her. “She said, ‘The work you're doing is very similar to what my team is doing at Amazon, and I think it would be really awesome if you came to work with us’,” Bryant recalls.

Sephus focuses on fairness and identifying biases in artificial intelligence, areas that Bryant was beginning to explore. She applied to the 2020 summer internship, went through the interview process, and got to work directly with Sephus.

During Bryant’s first AWS internship, she worked on bias auditing of services that estimate the expression of faces in images, an active area of research within academia and industry. In Bryant’s robotics healthcare research at Georgia Tech, the robots utilize emotion estimation to help identify what the patient they're working with is feeling in order to inform what they should do or say next.

This summer, during her second AWS internship, Bryant researched how to potentially improve the way the emotion being expressed on a person’s face is estimated. Other research within Amazon on emotion estimation entails making a determination of the physical appearance of a person's face. It is not a determination of the person’s internal emotional state. Currently, the way researchers generally train machine learning models for that type of estimation is by annotating numerous face images. Each image is labeled with a single emotion — happiness, sadness, surprise, disgust, or anger.

“We see that a lot of people disagree in their interpretations of the expressions on some faces. And what normally happens if a face has too many people disagreeing on the emotion it is expressing is that we throw it out of the dataset. We say it's not a good way to teach our models about emotion,” Bryant says. She thinks that maybe that’s exactly what the system should be learning. “We should be teaching it ambiguity just as much as we are teaching it about things of which we are absolutely sure.”

To that end, the team she was on explored letting people rate a series of emotions on a scale for each image, instead of labeling it with a single emotion. “Instead of throwing out the images, we can model that into a distribution that tells us: most people see this image as happy, but there is a significant amount of people who also see it as surprise.”

Even after the end of her internship, Bryant continues to work with her team to write a paper to describe some of the work they did over the last two summers.

“It's been a big project, but we have enough now that we're ready to put out a paper. So, I'm excited about that.”

Bryant recently got a return offer to come back to Amazon next summer, possibly to work on a partnership between Sephus’s team and the robotics team. “I haven't done anything with robotics at Amazon yet so I would actually love to see what they're doing over there, so the offer is very appealing.”

What robots should look like

Another area of research for Bryant is understanding how people conceptualize a robot based on its perceived abilities. There is an ongoing debate in robotics circles about whether developing humanoid robots is a good thing. Among other aspects, the controversy has to do with the fact that they are expensive to build and deploy.

“A lot of people are questioning: 'Do we even really need to be designing humanoids?’,” she says.

Bryant, along with colleagues at Georgia Tech who are interested in robots that are capable of perceiving emotions, designed an experiment to investigate how people imagine a robot’s appearance based on what it can do. The study’s participants worked on an emotion annotation activity with the assistance of an expert artificial intelligence system that followed a set of rules. The participants were told that “a robot is available to assist you in completing each task using its newly developed computer vision algorithm.”

De'Aira Bryant is seen from behind, she is typing on an open laptop and there is a humanoid robot with a display tablet on its chest looking at her to the right of the laptop
De'Aira Bryant and her colleagues at Georgia Tech designed an experiment to investigate how people imagine a robot’s appearance based on what it can do.
Courtesy of De'Aira Bryant

But the researchers did not tell them what the robot looked like. The robot’s predictions were provided via text. At the end of the study, participants were asked to describe how they envisioned it in their heads. Half of the people envisioned the robot with human-like qualities, with a head, arms, legs and the ability to walk, for example.

For that work – described in the article “The Effect of Conceptual Embodiment on Human-Robot Trust During a Youth Emotion Classification Task” — Bryant and her colleagues won the best paper award in the IEEE International Conference on Advanced Robotics and its Social Impacts (ARSO2021).

The goal of the research: investigate factors that influence human-robot trust when the embodiment of the robot is left for the user to conceptualize.

“In that paper, we presented the method of trying to gauge how humans expect a robot to look based on what it can do. That was one of the contributions,” says Bryant. The other contribution: demonstrate that it can be beneficial for a robot to look a certain way depending on its function. The study found that the participants who imagined the robot with human-like characteristics reported higher levels of trust than those who did not.

“For the robots that are emotionally perceptive, if we fail to meet the expectations of most people, then we could already be losing some of the effect that we intend to have,” says Bryant. “People expect that a robot that can perceive emotions will be human-like and if we don't design robots in that way, people could be less willing to depend on that robot.”

Future career plans

Bryant says that her long-term career plans are constantly changing. She was set on being a professor, but her experience at Amazon has redefined what industry research is for her. “On the last team I was on, I was actually working with a lot of professors. And I think it’s so cool to have the ability to bridge that gap.”

When she was about to start her first AWS internship, she expected she would be given a project, a few tasks, a deadline to complete them, and wouldn’t have a lot of say in that. “But when I first got there I actually did have a lot of say. They were interested in what I was doing at Georgia Tech, they wanted to know more about my research and made a strong effort to make the internship experience mine,” she says.

One of her ideas of a perfect job is being an Amazon Scholar. “I would get to work with students in a university and still work with Amazon. That is the perfect goal.”

Research areas

Related content

US, CA, Santa Clara
Job summaryAmazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology.Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Natural Language Understanding (NLU), Dialog management, conversational AI and Machine Learning (ML).As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding.We are hiring primarily in Conversational AI / Dialog System Development areas: NLP, NLU, Dialog Management, NLG.This role can be based in NYC, Seattle or Palo Alto.Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
IN, TS, Hyderabad
Job summaryAre you excited about driving business growth for millions of sellers by applying Machine Learning? Do you thrive in a fast-moving, large-scale environment that values data-driven decision making and sound scientific practices? We are looking for experienced data scientists to build sophisticated decision making systems that help Amazon Marketplace Sellers to grow their businesses.Amazon Marketplace enables sellers to reach hundreds of millions of customers and provides sellers the tools and services needed to make e-commerce simple, efficient and successful. Our team builds the core intelligence, insights, and algorithms that power a range of products used by millions of sellers. We are tackling large-scale, challenging problems such as helping sellers to prioritise business tasks by bringing together petabytes of data from sources across Amazon.You will be proficient with creating value out of data by formulating questions, analysing vast amounts of data, and communicating insights effectively to audience of varied backgrounds. In addition, you'll contribute to online experiments, build machine learning pipelines and personalised data products.To know more about Amazon science, Please visit https://www.amazon.scienceKey job responsibilities· Collaborate with domain experts, formulate questions, gather, process and analyse petabytes of data to unearth reliable insights· Design & execute experiments and analyze experimental results· Communicate insights effectively to audience of a wide range of backgrounds· Formulate relevant prediction problems and solve them by developing machine learning models· Partner with data engineering teams to improve quality of data assets, metrics and insights· Leverage industry best practices to establish repeatable science practices, principles & processes
US, NY, New York
Job summaryJob summaryAmazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology.Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Natural Language Understanding (NLU), Dialog management, conversational AI and Machine Learning (ML).As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding.We are hiring primarily in Conversational AI / Dialog System Development areas: NLP, NLU, Dialog Management, NLG.This role can be based in NYC, Seattle or Palo Alto.Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, VA, Arlington
Job summaryAmazon is investing heavily in building a world class advertising business and we are responsible for 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. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.Sponsored Products helps merchants, retail vendors, and brand owners succeed via native advertising that grows incremental sales of their products sold through Amazon. The Sponsored Products Ad Marketplace organization optimizes the systems and ad placements to match advertiser demand with publisher supply using a combination of machine learning, big data analytics, ultra-low latency high-volume engineering systems, and quantitative product focus. Our goals are to help buyers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and to build a major, sustainable business that helps Amazon continuously innovate on behalf of all customers.We are seeking a Sr. Applied Science Manager who has a solid background in applied Machine Learning and AI, deep passion for building data-driven products, ability to communicate data insights and scientific vision, and has a proven track record of leading both applied scientists and software engineers to execute complex projects and deliver business impacts.In this team, Machine Learning and Deep Learning technologies including Semantic Retrieval, Natural Language Processing (NLP), Information Extraction, Image Understanding, Learning to Rank are used to match shoppers' search queries to ads with per impression prediction models that run in real-time with tight latency budgets. Models are trained using self-supervised techniques, transfer learning, and supervised training using labeled datasets. Knowledge distillation and model compression techniques are used to optimize model performance for production serving.The Senior Manager role will lead science and engineering efforts in these areas for Amazon Search pages WW. The person in this role is responsible for: maintaining the consistent and long term reliability for the models and the delivery services that power them, managing diverse teams across multiple domains, and collaborating cross-functional with other senior decision makers. Our critical LPs for this role are Think Big, Are Right A lot, and Earns Trust. What is key is that the leader will need a dynamic mindset to build systems that are flexible and will scale.In this role, you will:· Lead a group of both applied scientists and software engineers to deliver machine-learning and AI solutions to production.· Advance team's engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner.· Develop science and engineering roadmap, run Sprint/quarter and annual planning, and foster cross-team collaboration to execute complex projects.· Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management.· Hire and develop top talents, provide technical and career development guidance to both scientists and engineers in the organization.Locations: Seattle, WA; New York, NY; Arlington, VA
US, WA, Seattle
Job summaryWorkforce Staffing (WFS) brings together the workforce powering Amazon’s ability to delight customers: the Amazon Associate. With over 1M hires, WFS supports sourcing, hiring, and developing the best talent to work in our fulfillment centers, sortation centers, delivery stations, shopping sites, Prime Air locations, and more.WFS' Funnel Science and Analytics team is looking for a Research Scientist. This individual will be responsible for conducting experiments and evaluating the impact of interventions when conducting experiments is not feasible. The perfect candidate will have the applied experience and the theoretical knowledge of policy evaluation and conducting field studies.Key job responsibilitiesAs a Research Scientist (RS), you will do causal inference, design studies and experiments, leverage data science workflows, build predictive models, conduct simulations, create visualizations, and influence science and analytics practice across the organization.Provide insights by analyzing historical data from databases (Redshift, SQL Server, Oracle DW, and Salesforce).Identify useful research avenues for increasing candidate conversion, test, and create well written documents to communicate to technical and non-technical audiences.About the teamFunnel Science and Analytics team finds ways to maximize the conversion and early retention of every candidate who wants to be an Amazon Associate. By focusing on our candidates, we improve candidate and business outcomes, and Amazon takes a step closer to being Earth’s Best Employer.
US, WA, Seattle
Job summaryAmazon Sub-Same-Day Supply Chain team is looking for an experienced and motivated Senior Data Scientist to generate data-driven insights influencing the long term SSD supply chain strategy, build the necessary predictive models, optimization algorithms and customer behavioral segments allowing us to discover and build the roadmap for SSD to enable operational efficiency and scale.Key job responsibilitiesWork with product managers, engineers, other scientists, and leadership to identify and prioritize complex problems.Translate business problems into specific analytical questions and form hypotheses that can be answered with available data using scientific methods or identify additional data needed in the master datasets to fill any gapsDesign, develop, and evaluate highly innovative statistics and ML modelsGuide and establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementationProactively seek to identify business opportunities and insights and provide solutions to shape key business processes and policies based on a broad and deep knowledge of Amazon data, industry best-practices, and work done by other teams.A day in the lifeIn this role, you will be a technical expert with significant scope and impact. You will work with Product Managers, Business Engineers, and other Scientists, to deeply understand SSDs current optimization strategy while benchmarking against industry best practices and standards to gain insights that will drive our roadmap. A successful Data Scientist will have extreme bias for action needed in a startup environment, with outstanding leadership skills, proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. It will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term scientific solutions. We are seeking someone who can thrive in a fast-paced, high-energy and fun work environment where we deliver value incrementally and frequently. We value highly technical people who know their subject matter deeply and are willing to learn new areas. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career.About the teamAmazon's Sub-Same Day (SSD) delivery program is designed to get customers their items as fast as possible – currently in as quickly as five hours. With ultra-fast delivery becoming increasingly important, we are looking for an experienced Senior Data Scientist to help us benchmark against industry standards to uncover insights to improve and optimize the long term supply chain strategy for Amazons Sub-Same-Day business.
US, NY, New York
Job summaryAmazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology.Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Natural Language Understanding (NLU), Dialog management, conversational AI and Machine Learning (ML).As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding.We are hiring primarily in Conversational AI / Dialog System Development areas: NLP, NLU, Dialog Management, NLG.This role can be based in NYC, Seattle or Palo Alto.Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, WA, Seattle
Job summaryAmazon's Weblab team enables experimentation at massive scale to help Amazon build better products for customers. A/B testing is in Amazon's DNA and we're at the core of how Amazon innovates on behalf of customers. We are seeking a skilled Applied Scientist to help us build the future of experimentation systems at Amazon.About you:You have an entrepreneurial spirit and want to make a big impact on Amazon and its customers. You are excited about cutting-edge research on unsupervised learning, graph algorithms, and causal inference in the intersection between Machine Learning, Statistics, and Econometrics. You enjoy building massive scale and high performance systems but also have a bias for delivering simple solutions to complex problems. You're looking for a career where you'll be able to build, to deliver, and to impress. You challenge yourself and others to come up with better solutions. You develop strong working relationships and thrive in a collaborative team environment.About us together:We're going to help Amazon make better long term decisions by designing and delivering A/B-testing systems for long-term experiments, and by using these systems to figure out how near term behavior impacts long term growth and profitability. Our work will inform some of the biggest decisions at Amazon. Along the way, we're going to face seemingly insurmountable challenges. We're going to argue about how to solve them, and we'll work together to find a solution that is better than each of the proposals we came in with. We'll make tough decisions, but we'll all understand why. We'll be the dream team.We have decades of combined experience on the team in many areas science and engineering so it's a great environment in which to learn and grow. A/B testing is one of the hottest areas of research and development in the world today and this is a chance to learn how it works in the company known for pioneering its use.
US, CA, Santa Clara
Job summaryAWS AI/ML is looking for world class scientists and engineers to join its AI Research and Education group working on building automated ML solutions for planetary-scale sustainability and geospatial applications. Our team's mission is to develop ready-to-use and automated solutions that solve important sustainability and geospatial problems. We live in a time wherein geospatial data, such as climate, agricultural crop yield, weather, landcover, etc., has become ubiquitous. Cloud computing has made it easy to gather and process the data that describes the earth system and are generated by satellites, mobile devices, and IoT devices. Our vision is to bring the best ML/AI algorithms to solve practical environmental and sustainability-related R&D problems at scale. Building these solutions require a solid foundation in machine learning infrastructure and deep learning technologies. The team specializes in developing popular open source software libraries like AutoGluon, GluonCV, GluonNLP, DGL, Apache/MXNet (incubating). Our strategy is to bring the best of ML based automation to the geospatial and sustainability area.We are seeking an experienced Applied Scientist for the team. This is a role that combines science knowledge (around machine learning, computer vision, earth science), technical strength, and product focus. It will be your job to develop ML system and solutions and work closely with the engineering team to ship them to our customers. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. You are also expected to work closely with other applied scientists and demonstrate Amazon Leadership Principles (https://www.amazon.jobs/en/principles).Strong technical skills and experience with machine learning and computer vision are required. Experience working with earth science, mapping, and geospatial data is a plus. Our customers are extremely technical and the solutions we build for them are strongly coupled to technical feasibility.About the teamInclusive Team CultureAt AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded scientist and enable them to take on more complex tasks in the future.Interested in this role? Reach out to the recruiting team with questions or apply directly via amazon.jobs.
US, CA, Santa Clara
Job summaryAWS AI/ML is looking for world class scientists and engineers to join its AI Research and Education group working on building automated ML solutions for planetary-scale sustainability and geospatial applications. Our team's mission is to develop ready-to-use and automated solutions that solve important sustainability and geospatial problems. We live in a time wherein geospatial data, such as climate, agricultural crop yield, weather, landcover, etc., has become ubiquitous. Cloud computing has made it easy to gather and process the data that describes the earth system and are generated by satellites, mobile devices, and IoT devices. Our vision is to bring the best ML/AI algorithms to solve practical environmental and sustainability-related R&D problems at scale. Building these solutions require a solid foundation in machine learning infrastructure and deep learning technologies. The team specializes in developing popular open source software libraries like AutoGluon, GluonCV, GluonNLP, DGL, Apache/MXNet (incubating). Our strategy is to bring the best of ML based automation to the geospatial and sustainability area.We are seeking an experienced Applied Scientist for the team. This is a role that combines science knowledge (around machine learning, computer vision, earth science), technical strength, and product focus. It will be your job to develop ML system and solutions and work closely with the engineering team to ship them to our customers. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. You are also expected to work closely with other applied scientists and demonstrate Amazon Leadership Principles (https://www.amazon.jobs/en/principles).Strong technical skills and experience with machine learning and computer vision are required. Experience working with earth science, mapping, and geospatial data is a plus. Our customers are extremely technical and the solutions we build for them are strongly coupled to technical feasibility.About the teamInclusive Team CultureAt AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded scientist and enable them to take on more complex tasks in the future.Interested in this role? Reach out to the recruiting team with questions or apply directly via amazon.jobs.