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?

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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.

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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.

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"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.

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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."

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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.

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Re-imagining the realms of what’s possible in advertising. Amazon is re-imagining advertising. Amazon Ads operates at the intersection of eCommerce and advertising and offering a rich array of advertising solutions and audience insights so businesses and brands can create relevant campaigns that produce measurable results. At Amazon Ads, you can build models that impact millions every day. And we’re passionate about solving real-world problems while using cutting-edge machine learning and artificial intelligence to do this. For example, our applied science teams leverage a variety of advanced machine learning and cloud computing techniques to power Amazon's advertising offerings. This includes building algorithms and cloud services using clustering, deep neural networks, and other ML approaches to make ads more relevant while respecting privacy. They develop machine learning models to predict ad outcomes and select the optimal ad for each shopper, context, and advertiser objective, leveraging techniques like multi-task learning, bandit/reinforcement learning, counterfactual estimation, and low-latency extreme ML. The teams also utilize Spark, EMR, and Elasticsearch to extract insights from big data and deliver recommendations to advertisers at scale, continuously improving through offline analysis and impact evaluation. Additionally, they apply generative AI models for dynamic creative optimization and video experimentation and automation. Underpinning these efforts are unique technical challenges, such as operating at unprecedented scale (hundreds of thousands of requests per second with 40ms latency) while respecting privacy and customer trust guarantees, and solving a wide variety of complex computational advertising problems related to traffic quality, viewability, brand safety, and more. Help us take innovation in advertising to the next level. Our teams are based in our fast-growing tech hubs in London and Edinburgh. Learn more about Amazon Ads, employee stories and available opportunities here: https://www.amazon.jobs/content/en/teams/advertising/applied-science-machine-learning-research?ref_=a20m_us_car_lp_asml Key job responsibilities * Design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both analysis and business judgment. * Collaborate with software engineering teams to integrate successful experiments into large-scale, highly complex Amazon production systems. * Promote the culture of experimentation and applied science at Amazon. * Demonstrate ability to meet deadlines while managing multiple projects. * Excel communication and presentation skills working with multiple peer groups and different levels of management * Influence and continuously improve a sustainable team culture that exemplifies Amazon’s leadership principles * Develop a deep and wide understanding of large ad tech solutions to which you will contribute, and how they interact with components owned by other teams. * Anticipate obstacles and look around corners, effectively prioritising work, solving trade-offs and influencing the development of advertising products beyond the scope of your immediate team. We are open to hiring candidates to work out of one of the following locations: Edinburgh, MLN, GBR | London, GBR
US, VA, Arlington
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center at AWS is a new strategic team that helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Data Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. A key focus of this role is GenAI model customization using techniques such as fine-tuning and continued pre-training to help customers build differentiating solutions with their unique data. Key job responsibilities As a Data Scientist, you will: Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder Provide customer and market feedback to Product and Engineering teams to help define product direction About the team Sales, Marketing and Global Services (SMGS) AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest-growing small- and mid-market accounts to enterprise-level customers, including the public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. The Professional Services team is part of Global Services. About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Denver, CO, USA | Herndon, VA, USA | New York, NY, USA | Santa Clara, CA, USA | Seattle, WA, USA | Washington Dc, DC, USA