Sergey Menis is seen outside on a sunny day with a colorful landscape of mountains behind him, Sergey is standing to the left with his arms crossed, looking into the camera
Sergey Menis developed the nanoparticle platform that underpins a promising HIV vaccine candidate. The nanoparticle Menis designed snaps together with a protein, eOD-GT8, which is optimized to stimulate production of the rare antibodies that can eventually become bnAbs.
Courtesy of Sergey Menis

Amazon scientist Sergey Menis contributes to development of vaccine approach against HIV

"I hope we have accelerated HIV vaccine development by providing findings that we and others can build on."

About 16 years ago, Sergey Menis was volunteering at a protein design lab during the day and parking cars at night. He'd come to the Baker Lab in Seattle on a whim. While earning his master's degree in bioinformatics at Chalmers University of Technology in Sweden, he read a 2003 paper describing the lab's work designing a novel protein that didn't exist in nature.

"I was just in awe of that power," Menis recalled. He wanted to learn more about biochemist David Baker's work and emailed asking to join the lab, which is based at the University of Washington. Once there, he opted to work with Bill Schief, a postdoctoral researcher with Baker who was just starting his own lab. But Schief noticed Menis wasn't fully present in his work — he often seemed sleepy. What was going on?

Related content
Using social media data, the University of Maryland's Philip Resnik aims to help clinicians prioritize individuals who may need immediate attention.

Menis explained about the night job at the car park. He wanted to do more at the lab, but after all, he had to pay rent. Schief asked how much Menis needed to cover his expenses. Then he hired him.

That job was a turning point.

Schief and his team, along with Menis, developed a breakthrough approach to a vaccine for HIV. In February 2021, the nonprofit scientific research organizations IAVI and Scripps Research announced exciting results in a phase 1 clinical trial — called IAVI G001 — of the Schief lab's vaccine candidate. A phase I trial represents the first time a vaccine is tested in humans, one step in what is typically a four-phase process that determines its safety, efficacy, and proper dosage. In this case, the promising vaccine produced the desired immune response in 97% of participants.

HIV vaccine approach succeeds in first clinical trial

Earlier this year, building on those results, IAVI and Moderna announced that first doses had been administered in a new clinical trial of the experimental HIV vaccine. IAVI officials noted this portion of the phase 1 trial, called IAVI G002, will test the ability to prime and further mature the desired immune response using Moderna’s messenger RNA (mRNA) delivery platform used for their coronavirus vaccines. The mRNA platform enables rapid vaccine production that may dramatically accelerate the development timeline.

Guided by curiosity

Menis, who joined Amazon as a scientist in November 2020 and is now a solution architect with Amazon Web Services (AWS), hadn't set out to be a biomedical researcher, or even a scientist. "I never had a career in mind, in general," he said. "I would just follow whatever looked interesting."

As an undergrad at the University of Florida, that meant computer science. It wasn't until he had obtained his master's degree in software engineering and begun working at the defense and aerospace company Lockheed Martin that he started to rethink his career path.

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

Writing software for government contract projects was fine, but it didn't feel hands-on enough. "I wanted to see more feedback and results, faster," Menis said.

He recalled a bioinformatics elective class that he'd taken while in grad school at the University of Central Florida. On another fateful impulse, he decided to look at bioinformatics grad programs; this time in Europe, as he was in search of a change of scenery. He got accepted to Chalmers University of Technology and, without knowing much about the university, headed to Sweden.

"Even though it's a well-known school in certain circles, I wasn't even sure it was a real school until I arrived there," he said, laughing. "But it turned out to be a fantastic school and a really intense program."

And when he read about David Baker's work in inventing a protein molecule from scratch, the next chapter of his career — computational protein design — began to unfold.

HIV: a formidable foe

Human immunodeficiency virus has infected more than 75 million people and killed more than 32 million since the epidemic began in early 1980s. With the isolation of the virus in the mid-1980s, it seemed that a vaccine was in the offing. But conventional approaches, which involve taking some inactivated part of the virus to stimulate an immune response, have not worked for HIV.

The virus has multiple wily strategies it employs to hide within the body. It cloaks itself with sugars that make it nearly invisible to the human immune system. And its surface is always changing, a series of disguises that fool most enemy antibodies. But researchers have identified a ray of hope buried within the immune system: the potential to make bnAbs, which can recognize and defeat 99% of HIV strains.

Sergey Menis is seen in a lab setting, wearing gloves while holding a device
Sergey Menis said when he read about David Baker's work in inventing a protein molecule from scratch, the next chapter of his career — computational protein design — began to unfold.
Courtesy of Sergey Menis

The problem is, people don't develop bnAbs until they're years into an infection. “That's too little, too late," Menis said. "By the time you've actually started developing the responses you need, you're already productively infected."

The strategy researchers are pursuing is to initiate the process of making these potent antibodies before infection occurs, giving the body a head start. To do so, they must identify the right "baby antibodies," as Menis calls them, and train them to be bnAbs.

Given that the human body has the ability to make an estimated 1 quintillion unique antibodies, finding and training the right ones is a needle-in-the-haystack endeavor. And only certain antibodies have the ability to become bnAbs—those baby antibodies are literally one in a million.

Only a small fraction of people with HIV develop the most potent bnAb response — the kind an effective vaccine would elicit — on their own. Researchers have been able to zero in on these antibodies by analyzing blood from HIV-positive donors. But there's good news, and the recent clinical trial confirmed it.

Related content
Politecnico di Milano professor Stefano Ceri is working to integrate genomic datasets into a single accessible system with the support of an Amazon Machine Learning Research Award.

"Nearly everyone in the world should have the cells needed to start the process of producing this immune response," Menis said. "To get that process started, we need to find them, stimulate them, and have them multiply."

Building a vaccine platform

After Menis began working at Baker Lab, he decided to pursue a PhD in biochemistry at the University of Washington in the Schief lab. Menis moved to San Diego midway through his PhD studies when Schief moved his lab to Scripps Research and IAVI.

"Sergey is very thoughtful and calm, with meticulous attention to detail. He is curious about how things work," said Schief, who is executive director of vaccine design for IAVI’s Neutralizing Antibody Center (NAC) at Scripps Research and a professor in the Department of Immunology and Microbiology at Scripps.

Schief advised Menis on his PhD thesis, during which Menis developed the nanoparticle platform that underpins the HIV vaccine candidate. The nanoparticle Menis designed snaps together with a protein, eOD-GT8, which is optimized to stimulate production of the rare antibodies that can eventually become bnAbs. The eOD-GT8 protein was developed primarily by another PhD student in the Schief lab, Joe Jardine. The nanoparticle amplifies the body's response by delivering multiple copies of eOD-GT8.

A computer image of the eOD-GT8 immune-stimulating protein.
A computer image of the eOD-GT8 immune-stimulating protein.
Courtesy of Sergey Menis

"It's spherical, like a virus, so the immune system treats it as if it might be a virus of some kind," Menis said. "We want to make it look like a little virus, even though it has no infectious properties whatsoever."

Menis served as the Schief lab's subject matter expert during the multi-year process of developing the vaccine candidate. "He played a big role in planning and carrying out the clinical trial," Schief said.

A team effort

Both Menis and Schief are careful to emphasize that there is much more to do before an approved HIV vaccine becomes reality. While the results from IAVI G001 are encouraging, there are significant milestones remaining.

"By demonstrating that this concept works in humans, and actually can work very well in terms of eliciting strong and consistent responses of the kind we wanted, I hope we have accelerated HIV vaccine development by providing findings that we and others can build on," Schief said.

Related content
Amazon Research Award recipient Jonathan Tamir is focusing on deriving better images faster.

Menis is also quick to credit the 48 volunteers who participated in the IAVI G001 clinical trial, noting that without such volunteers, a vaccine wouldn’t be possible. "They are the co-creators of this effort," he said. Schief and Menis also praised the work of many other individuals, particularly colleagues at Fred Hutch, George Washington University, and the NIH Vaccine Research Center.

The upcoming IAVI G002 will recruit 56 volunteers across four sites: GWU School of Medicine and Health, Hope Clinic of Emory Vaccine Center in Atlanta, Fred Hutchinson Cancer Research Center in Seattle, and the University of Texas–Health Science Center at San Antonio. The goal: replicate the priming of “baby antibodies” observed in IAVI G001 and teach them to take a step towards becoming a bnAb capable of neutralizing HIV.

An intriguing offer

Menis was working at IAVI and preparing to go on vacation when Amazon contacted him in 2020, asking whether he'd be interested in a position at the company. The hiring process happened quickly: He did an interview while on the trip, and on his first day back from vacation, he had an offer in his inbox.

"When Amazon reached out, I was really intrigued by the possibilities of what a giant like Amazon could be doing," Menis said. "I was open to discovering what that meant."

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.

After spending a little over a year as a research scientist, Menis moved into a senior product manager role with Amazon Diagnostics and then transitioned into a role as a solution architect with AWS, building solutions for healthcare and life sciences startups. “For me, the roles represent opportunities to learn and be curious,” Menis said, citing one of Amazon’s leadership principles.

He admitted he didn’t know much about the principles until his first job interview, but now he has come to appreciate them. He enjoys seeing how they relate to him and his past work.

“Working at Amazon has been a learning experience,” he says — yet another on the journey from lab volunteer to medical-breakthrough-creating scientist to whatever the next chapter will be.

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

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.
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, 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.
US, WA, Seattle
Job summaryHow can we create a rich, data-driven shopping experience on Amazon? How do we build data models that helps us innovate different ways to enhance customer experience? How do we combine the world's greatest online shopping dataset with Amazon's computing power to create models that deeply understand our customers? Recommendations at Amazon is a way to help customers discover products. Our team's stated mission is to "grow each customer’s relationship with Amazon by leveraging our deep understanding of them to provide relevant and timely product, program, and content recommendations". We strive to better understand how customers shop on Amazon (and elsewhere) and build recommendations models to streamline customers' shopping experience by showing the right products at the right time. Understanding the complexities of customers' shopping needs and helping them explore the depth and breadth of Amazon's catalog is a challenge we take on every day. Using Amazon’s large-scale computing resources you will ask research questions about customer behavior, build models to generate recommendations, and run these models directly on the retail website. You will participate in the Amazon ML community and mentor Applied Scientists and software development engineers with a strong interest in and knowledge of ML. Your work will directly benefit customers and the retail business and you will measure the impact using scientific tools. We are looking for passionate, hard-working, and talented Applied scientist who have experience building mission critical, high volume applications that customers love. You will have an enormous opportunity to make a large impact on the design, architecture, and implementation of cutting edge products used every day, by people you know.Key job responsibilitiesScaling state of the art techniques to Amazon-scaleWorking independently and collaborating with SDEs to deploy models to productionDeveloping long-term roadmaps for the team's scientific agendaDesigning experiments to measure business impact of the team's effortsMentoring scientists in the departmentContributing back to the machine learning science community
US, NY, New York
Job summaryAmazon Web Services is looking for world class scientists to join the Security Analytics and AI Research team within AWS Security Services. This group is entrusted with researching and developing core data mining and machine learning algorithms for various AWS security services like GuardDuty (https://aws.amazon.com/guardduty/) and Macie (https://aws.amazon.com/macie/). In this group, you will invent and implement innovative solutions for never-before-solved problems. If you have passion for security and experience with large scale machine learning problems, this will be an exciting opportunity.The AWS Security Services team builds technologies that help customers strengthen their security posture and better meet security requirements in the AWS Cloud. The team interacts with security researchers to codify our own learnings and best practices and make them available for customers. We are building massively scalable and globally distributed security systems to power next generation services.Inclusive Team Culture Here 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. 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 Balance Our 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 Growth Our 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. We care about your career growth and strive to assign projects based on what will help each team member develop and enable them to take on more complex tasks in the future.A day in the lifeAbout the hiring groupJob responsibilities* Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment.* Collaborate with software engineering teams to integrate successful experiments into large scale, highly complex production services.* Report results in a scientifically rigorous way.* Interact with security engineers, product managers and related domain experts to dive deep into the types of challenges that we need innovative solutions for.
US, NY, New York
Job summary**This job is also open for New York and Palo Alto**This position will be part of the Marketplace Intelligence organization within Sponsored Products. Our team focuses on determining operating points of Sponsored Products to provide efficient and customized shopping experience for shoppers and increased discoverability and business growth for selling partners by developing new measurements, economics methodology, and state-of-the art machine learnt optimization technologies. Our systems, algorithms and strategies operates on one of the most sophisticated advertising marketplaces that evolves from impression to impression and changes from one marketplace to another, across segments of traffic and demand. Key job responsibilitiesAs a seasoned leader, you will build and manage an inter-disciplinary team with scientists, economists, and engineers to develop and manage monetization controls for SP marketplace. The leader will set the vision of pricing strategy, build engineering system and large scale machine learning and optimization models. These models will continuously change operating points based on the feedback of marketplace, shopper and advertisers.This is a rare and exciting opportunity to be a trailblazer at the intersection of cutting edge science, economics, game theory and engineering to impact millions of advertisers. As a hands-on leader of this team, you will be responsible for defining long term business strategies, answer key research questions, discover investment opportunities, develop and deploy innovative machine learning solutions and deliver business results. You will also participate in organizational planning, hiring, mentoring and leadership development. You will be technically fearless and build scalable science and engineering solutions.
US, WA, Seattle
Job summaryThe Amazon Product Classification and Inference Services team is seeking a Sr. Applied Science Manager for leading initiatives for understanding, classifying and inferring product information. Our vision is simple: build AI systems that are capable of a deep product understanding, so we can organize and merchandise products across the Amazon e-commerce catalog worldwide. You will lead a team of experienced Applied Scientists (direct reports) and also a Manager of Applied Science to create models and deliver them into the Amazon production ecosystem. Your efforts will build a robust ensemble of ML techniques that can drive classification of products with a high precision and scale to new countries and languages. The leader will drive investments in cutting edge machine learning: natural language processing, computer vision and artificial intelligence techniques to solve real world problems at scale. We develop Deep Neural Networks as our your daily job and use the team's output to affect the product discovery of the biggest e-tailer in the world. The research findings are directly related to Amazon’s Browse experience and impact million of customers. The team builds solutions ranging from automatic detection of misclassified product information in the ever growing Amazon Catalog, applications for inferring and backfilling product attributes (processing images, text and all the unstructured attributes) in the Amazon catalog to drive true understanding of products at scale. We are looking for an entrepreneurial, experienced Sr. Applied Science Manager who can turn a group of Machine Learning Scientists and Managers (PhD's in NLP, CV) to produce best in class solutions. The ideal candidate has deep expertise in one or several of the following fields: Web search, Applied/Theoretical Machine Learning, Deep Neural Networks, Classification Systems, Clustering, Label Propagation, Natural Language Processing, Computer Vision. S/he has a strong publication record at top relevant academic venues and experience in launching products/features in the industry.Key job responsibilitiesIn this team, you will:Manage business and technical requirements, design, be responsible for the overall coordination, quality, productivity and will be the primary point of contact for world-wide stakeholders of programs and goals that you lead.Partner with scientists, economists, and engineers to help deliver scalable ML scaled models, while building mechanisms to help our customers gain and apply insights, and build road maps for the projects you own.Track service levels and schedule adherence, and ensure the individual stakeholder teams meet and exceed their performance targets.Be expected to discover, define, and apply scientific, engineering, and business best practices.Manage and develop Scientists (direct reports and a Science Manager with a respective team).A day in the lifeYou will lead an Amazon team that builds creative solutions to real world problems. Your team will own devising the strategy and execution plans that power initiatives ranging from: classifying all Amazon products, fact extraction, automatic detection of missing product information, active learning mechanisms for scaling human tasks, building applications for understanding what type of information is critical, building mechanisms to analyze product composition, ingest images, text, and unstructured data to drive deep understanding of products at scale. About the teamThe team's mission is to infer knowledge, understand, classify, derive product facts for all Amazon products entering the Catalog. The work is critical to power the Amazon Taxonomy, Search, Navigation and Detail Page experiences, impacting million of customers. This is an already formed team with experience leading programs spanning services and ML initiatives supporting all countries and languages. The leader collaborates closely with Software Managers, Sr. Leaders, and has exposure to multiple peer teams at Amazon who rely on this team's developments.
US, MA, Westborough
Job summaryAre you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers who work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling, and fun.Amazon.com empowers a smarter, faster, more consistent customer experience through automation. Amazon Robotics automates fulfillment center operations using various methods of robotic technology including autonomous mobile robots, sophisticated control software, language perception, power management, computer vision, depth sensing, machine learning, object recognition, and semantic understanding of commands. Amazon Robotics has a dedicated focus on research and development to continuously explore new opportunities to extend its product lines into new areas.This role is a 3-month internship to join AR full-time (40 hours/week) from May 22, 2023 to August 25, 2023. This Amazon Robotics internship opportunities will be Hybrid (2- 3 days onsite) and based out of the Greater Boston Area in Westborough, MA. The campus provides a unique opportunity to have direct access to robotics testing labs and manufacturing facilities.About the teamWe are seeking data scientist interns to help us analyze data, quantify uncertainty, and build machine learning models to make quick prediction.
US, WA, Seattle
Job summaryDo you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day.Major responsibilities Use statistical and machine learning techniques to create scalable risk management systemsLearning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trendsDesign, development and evaluation of highly innovative models for risk managementWorking closely with software engineering teams to drive real-time model implementations and new feature creationsWorking closely with operations staff to optimize risk management operations,Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementationTracking general business activity and providing clear, compelling management reporting on a regular basisResearch and implement novel machine learning and statistical approaches