Dr. Kristina Simonyan
“For patients it's just really scary,” says Dr. Kristina Simonyan, a neuroscientist and the head of the Dystonia and Speech Motor Control Laboratory at Massachusetts Eye and Ear and Harvard Medical School. “It’s one thing if you know what your issue is—but not to know is very difficult in any health diagnosis.”
Credit: Anna Olivella

Amazon Research Award recipient develops new tool to diagnose dystonia

Dr. Kristina Simonyan and her team created an AI-based deep learning platform that offers patients some peace of mind.

Imagine waiting five years to get a diagnosis. That is the reality facing those who may be battling dystonia, a potentially debilitating neurological condition that requires a painstaking process to identify. Dystonia is characterized by involuntary muscle movements that can manifest throughout the body, but usually show up in one area. Commonly, eyelid muscles, neck muscles, hands, or vocal cords are affected—all of which can seriously interfere with people’s lives. For example, laryngeal dystonia, which impacts the voice, can make speech difficult or impossible.

Symptoms often first appear in midlife, when patients are hitting career highs and family pressures mount. “For patients it’s just really scary,” says Dr. Kristina Simonyan, a neuroscientist and the head of the Dystonia and Speech Motor Control Laboratory at Massachusetts Eye and Ear and Harvard Medical School. “It’s one thing if you know what your issue is—but not to know is very difficult in any health diagnosis.”

The long and difficult diagnosis time, which takes an average of five-and-a-half years for a typical patient, is exactly why her laboratory spent the last decade-plus developing DystoniaNet, a new AI-based deep learning platform that can perform the task in a fraction of a second.

Dystonia is considered a rare disorder; it affects about 300,000 people in the United States. It’s also often undiagnosed or misdiagnosed, so the actual numbers may be higher. Why is it so tough to know if someone has it? There’s no biomarker or gold-standard diagnostic test for dystonia, so doctors have to go through a process of elimination to determine whether the symptoms suggest dystonia or another neurological issue, like Parkinson’s. Even that process isn’t straightforward: “The clinical criteria are vague, and they’re not standardized. They depend on the clinician’s experience and expertise,” Simonyan says.

Symptoms also vary between patients—and even within the same patient—and can fluctuate over time. “If [a patient] sees the clinician in the morning and then sees another clinician that afternoon, there could be a discrepancy in opinions, because symptoms also change at different times of the day and different days within the week,” says Simonyan.

Those challenges are exactly why a dystonia diagnostic test is so important to develop.

Simonyan’s work on dystonia began in 2004, when she was a postdoctoral researcher with the National Institutes of Health. Her interest in laryngology, which began in medical school when she became fascinated by hearing and voice production, led her to focus on neural control of voice production and then laryngeal dystonia—but she was starting from scratch.

“There was really nothing known,” Simonyan says. “At that time, there weren’t any neuroimaging studies done to see where the abnormalities are, what is normal or abnormal, or how voice and speech are processed and output by the brain in these patients.”

She published paper after paper on research aimed at figuring out the functional and structural abnormalities in the brains of patients with laryngeal dystonia, as well as the connectivity between brain regions and speech production. “For many, many years, we were trying to understand the pathophysiology of this disorder in order to identify better diagnostic and better treatment options,” says Simonyan.

Four years ago, all that work started to pay off.

For patients with dystonia, an MRI usually doesn't show an abnormality specific to the disease, says Simonyan. But over time, radiological images acquired for research studies consistently picked up hallmarks of dystonia within the brain—microstructural changes that a clinical MRI wouldn’t show. “We capitalized on that,” she says. 

In 2016, Simonyan and her research team published their first paper using machine learning linear discriminant analysis (LDA). LDA is a method used to classify a set of data into distinct groups—in this case the structural and functional MRI neuroimaging of different phenotypes and genotypes of dystonia. Once those markers were identified and categorized from a large number of patients, they were fed into a machine learning algorithm.

The goal, Simonyan says, was to see whether images from patients already diagnosed with dystonia could be used to classify undiagnosed patients who might have the disease. It worked, with a success rate of 81% correct diagnoses. That’s better than the current rate among physicians (about 34%), but still not good enough to move to clinical setting—and it meant doctors treating patients needed to learn how to do time-consuming image analysis and other tasks to run the program.

Time in the clinic is limited and the busy doctors there have other priorities. Simonyan wanted an even better test. “That was my motivation to turn this research to deep learning,” she says. Her team set out to build a tool that automated everything—not only the machine learning analysis of data, but the data input and processing as well.

Together with her postdoctoral fellow, she did just that over the past two years, increasing the level of automation in several iterations. “With the support of Amazon Web Services, we were fortunate to have access to superb computational resources and combine them with our large data set of patients. The final product was DystoniaNet,” she says.

And while the data were centered on laryngeal dystonia, the test also works to diagnose other forms of dystonia that affect the neck muscles (cervical dystonia) or eyelid muscles (blepharospasm). It has a correct diagnosis rate of 98.8%, and best of all, it doesn’t take years or months: Simonyan’s test takes just .36 seconds.

Simonyan hopes that DystoniaNet will move to clinical practice (expanded testing is underway) and says clinicians and researchers have been very excited at her presentations.

In the meantime, her team continues to refine DystoniaNet. A new capability would incorporate the ability to rule out dystonia and pinpoint other neurological disorders, such as Parkinson’s and essential tremor, making it useful to many more physicians—and patients.

DystoniaNet doesn’t exclude the physician from the process of diagnosis, Simonyan says: “It just helps them and provides an objective diagnostic tool that they have been lacking all this time.”

Our goal is to support researchers, such as Dr. Simonyan and her team, with infrastructure and tools to accelerate their work through the Amazon Research Awards program.
Taha A. Kass-Hout, MD, MS, director of machine learning, at Amazon Web Services

She says Amazon's ARA funding for her work on DystoniaNet was critical. Her team was able to hire additional help and it gave them access to the cloud, where they could speed up the process of training and testing the model.

“That really made a difference for us to move forward, especially with the very large number of subjects,” she says.

Computing power made a difference too: The computational framework Simonyan’s team used was implemented on an AWS Deep Learning Amazon Machine Image (AMI), and run on the Amazon Web Services EC2 P2, which Simonyan says wasn’t matched by even the very powerful workstations in her lab. That expanded the computational ability to test, train, and refine different iterations of the model. Without that capability, she says, “our time in this process would have been much, much longer—we probably would have been still testing it,” she says.

Her team’s ability to harness the potential of AWS also factored into the decision to fund her grant.

“Our goal is to support researchers, such as Dr. Simonyan and her team, with infrastructure and tools to accelerate their work through the Amazon Research Awards program,” says Taha A. Kass-Hout, MD, MS, director of machine learning, at Amazon Web Services. “We are thrilled to hear that AWS machine learning tools were able to speed up their groundbreaking research and development of DystoniaNet.”

Even with Simonyan’s work, hurdles remain for dystonia patients. The cause is unknown, there is no cure, and available treatments are minimal. All patients can do is work with their doctor to manage their symptoms. But knowing exactly what disease they have, and that it’s not fatal even though it affects their quality of life, can reduce some of the fear and uncertainty for those who suffer from it.

“They go through this period of time where they don’t know if they're dying or not, or what's wrong with them,” says Simonyan. “So all of them are relieved when they get the diagnosis.”

View from space of a connected network around planet Earth representing the Internet of Things.
Sign up for our newsletter

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.