Amazon Glamazon Gay Pride Month LGBTQIA+ Black Lives Matter
From top left to bottom right: Luyolo Magangane, applied scientist; Ruiwei Jiang, research scientist; Sheeraz Ahmad, applied scientist; Liz Dugan, user experience researcher; Shane McGarry, data scientist; Abhinav Aggarwal, applied scientist.
Credit: Glynis Condon

Pride and prejudice: 6 Amazon scientists share their experiences

Scientists from glamazon, Amazon’s LGBTQIA+ affinity group, say this year's Pride Month is as much about solidarity as it is about celebration.

In most cities around the world June is considered Pride Month, where people celebrate diversity and inclusion. It usually culminates in a parade or march to promote the self-affirmation, equality, and visibility of the lesbian, gay, bisexual, transgender, queer or questioning, intersex, and asexual or allied (LGBTQIA+) community.

At Amazon, it's no different. There's a community of more than 7,000 employees from across the globe who are part of glamazon, an affinity group and employee network, whose mission is to connect those interested in LGBTQIA+ issues to company resources and to each other and to showcase Amazon’s acceptance in communities worldwide.

Given current events, particularly global protests resulting from the videotaped killing of George Floyd by law enforcement officials and the recent U.S. Supreme Court ruling upholding LGBTQIA+ equality, we asked some of the scientists within this affinity group about the significance of this year’s Pride Month.

Abhinav Aggarwal, applied scientist, Alexa Trust

Abhinav Aggarwal (pronouns: he/him/they/them) joined Amazon about nine months ago, after obtaining his PhD in computer science from the University of New Mexico in 2019. His work focuses on building customer trust by designing privacy-preserving machine learning algorithms for handling customer data.

Abhinav Aggarwal, applied scientist, Alexa Trust
Abhinav Aggarwal, applied scientist, Alexa Trust

“Since I joined Amazon, I’ve only had a very passive interaction with glamazon through emails. But I feel like the variety of topics discussed there is absolutely amazing. It’s not just LGBTQIA+ issues; there are thoughts about body positivity, gender pronouns, having pronouns on badges, and issues around diversity and inclusion,” he said.

“But I’d like to see more gender-neutral restrooms in the buildings and use of the ‘they’ pronoun by default,” he says. “Whenever I refer to someone I don’t personally know or even know of at all, I default to using ‘they/them’ as a pronoun. It would be nice to see this as common practice and not assuming someone’s gender based on familiarity with the name, which aligns with the removal of unconscious bias and helps with acceptance.”

With privacy and fairness in AI becoming an increasingly important topic, Aggarwal sees similar issues within his field.

“You don’t want your models for services like Alexa to give you results that are gender-biased, especially as we move towards a more gender-neutral world,” Aggarwal explains. “Ideally, our models should produce gender-agnostic results, and we must work backwards from this goal when defining gender-based fairness. That’s something I’ve felt a lot of pushback with within the industry, because the problem becomes far more complex if you talk about gender neutrality and the continuous spectrum of gender, instead of just the binary male or female.”

Aggarwal sees celebrating Pride Month as a step towards this awareness.

“I think these movements are absolutely necessary because they call out basic human rights against discrimination. They call out a very fundamental way of how we think we should be treated. LGBTQIA+ is a tag to help identify and understand ourselves better. It doesn’t change who we are as a person. It doesn’t change how technically advanced or skilled we are. It doesn’t change how we are going to perform at Amazon,” Aggarwal emphasizes.

“If the person is a good human being at heart, helps society and contributes to the general well-being of the nation, that’s what’s more important, independent of whether they are gay, lesbian, Black, white or associate themselves in any other way. Acknowledgement of this label-agnostic human existence is much more than man-made tags.”

Sheeraz Ahmad, applied scientist, Amazon SageMaker Ground Truth

Sheeraz Ahmad (pronouns: he/him) joined Amazon more than four years ago as a research scientist. Today, he works as an applied scientist on Amazon SageMaker Ground Truth team, an AWS data-labeling service that makes it easy to build highly accurate training data sets for machine learning.

Sheeraz Ahmad, applied scientist, Amazon SageMaker Ground Truth
Sheeraz Ahmad, applied scientist, Amazon SageMaker Ground Truth

Prior to Amazon, he received his PhD in computer science from the University of California San Diego (UCSD), where he focused on computational modeling of human and animal behavior in different domains, with the goals of gaining insights into the inner workings of the brain and developing behaviorally inspired machine learning models.

Ahmad, who grew up in Kanpur, India, previously earned his bachelor’s degree in electrical engineering from the prestigious Indian Institute of Technology Kanpur.

In Kanpur, Ahmad's experience was that being on the LGBTQIA+ spectrum was not well accepted, and he didn’t have many role models to follow. That changed after college when he moved to a larger city, Bangalore, and especially when he attended UCSD, where “I came across people who were out and proud and doing amazing things in life.”

Now, as an active member of Amazon’s glamazon affinity group, Ahmad is a role model himself. When he first joined Amazon, he appreciated glamazon’s support and attended events but found socializing difficult in some of the larger events. So for more than four years now, he’s organized monthly game nights, where a smaller group of glamazon members in Seattle get together to socialize and play board games. Even during the COVID-19 pandemic the tradition has continued, though online.

Pride Month is especially meaningful to Ahmad, but this year “the tone is more somber, understandably so.”

“There’s a lot going on, and as much as there is to celebrate, there’s so much more to be done. This month, as a gay man, my focus is more on being an ally for people who are going through their own struggles,” he says. “Gay men have faced discrimination and hardship, and we need to lean into those experiences, remember all the pain we’ve gone through, and be there for the womxn and our African-American brothers and sisters.

“I’m sharing with my friends, who tend to be somewhat conservative, how I have felt, based on my own experiences, and trying to relate how all members of the LGBTQIA+ community are feeling now, especially those who are African American. It’s important to be there for them, to be an ally, providing solidarity.”

“This year," Ahmad says, “feels less about celebration and more about solidarity.”

Liz Dugan, user experience researcher, Amazon Alexa

Liz Dugan (pronouns: she/her) joined Amazon earlier this year and during her onboarding experience learned about the glamazon affinity group. The voice user interface researcher, who earned a bachelor’s degree in psychology and a master’s degree in cognitive psychology from the University of Oklahoma, self-identifies as a queer, bisexual woman. She immediately felt welcomed by glamazon members.

Liz Dugan, user experience researcher, Amazon Alexa
Liz Dugan, UX researcher, Amazon Alexa

“Since I’ve been here, I’ve noted more and more people joining the group, and everyone is treated the same. People reach out and say, ‘How can we help you? Is there anything we can provide you? Please let us know if there’s anything you need.’ So you immediately feel as though this is a safe place.”

On this day, despite recent events, Dugan is more upbeat, as the Supreme Court has just ruled that a landmark civil-rights law protects gay and transgender workers from workplace discrimination. “An employer who fires an individual merely for being gay or transgender defies the law,” Justice Neil M. Gorsuch wrote for the majority in the court’s 6-to-3 ruling.

“So the LGBTQIA+ community just had a very historic win today. We wouldn’t be experiencing the moment we are today without Stonewall,” she says, referring to the 1969 New York City Stonewall riots that are considered one of the most important events leading to today’s fight for LGBTQIA+ rights.

“Everything we have today started with Stonewall, which was a riot started by trans people of color. So today we can live publicly and authentically and mostly safe from verbal abuse because of Black trans activists. Yet today we are still seeing those same populations being actively targeted and murdered without any real recourse or much publicity. Just within the past few days two Black trans women were murdered, and I’ve seen no one talk about it.”

“Some of the freedoms we enjoy today are because of Black trans women, and yet we continue to fail them as a privileged group of gay mostly white individuals, and we’re not doing enough to support the Black Lives Matter movement now. …We need to return to our roots and lift up our brothers and sisters who are suffering. They started the movement for us, and we need to be there for them now.”

Like other colleagues, Dugan feels like this year’s Pride Month is less a time to celebrate and more a time to continue pushing for progress.

“It’s a moment to return to our community’s roots. We still have problems,” she says. “We still have youth who don’t have homes and are struggling; we still have people who are discriminated against; we still have people who are being brutalized and murdered. So while we can be proud of what we’ve accomplished, we still have work to do. We have to carry our pride but still get our hands dirty. Stonewall wasn’t a celebration. Stonewall was a riot. So we have to keep fighting.”

Ruiwei Jiang, research scientist, Alexa Domains - HHO

Before joining Amazon as a research scientist, Ruiwei Jiang (pronouns: she/her) studied computational genetics in college, working in particular on human DNA. Her studies explored the adverse impact of pollution on human genetic encoding, comparing the short- and long-term effects of living in a polluted versus non-polluted environment.

Ruiwei Jiang, research scientist, Alexa Domains
Ruiwei Jiang, research scientist, Alexa Domains

“It might not sound super relevant to Alexa, but you're doing computation decks, working with a lot of data, writing code and doing a lot the analysis and building out of models, so that sort of became transferable knowledge,” she says.

Her role within the Alexa Household Organization, whose mission is to help Alexa help families stay organized and connected with one another, is to maintain the natural-language-understanding framework for features such as reminders, calendar tasks, weather, and recipes, as well as for creating models to improve customer retention.

“The world is moving towards conversational AI,” she says, “and it’s cool to be able to say you’re working in this field and developing models that are actually being used by customers, who are directly benefiting from it.”

Jiang is based in Amazon’s Vancouver office, where she’s experienced many positive actions from the glamazon affinity group, which have warmed her heart.

“They organize meetings in the office on a Sunday afternoon or Saturday morning, before the Pride parade, and hand out stickers. It’s a small thing, but it all adds up. Previous companies I’ve worked at have never really stood up as a corporation and been like ‘hey, we’re going to do something together for the Pride parade’. But at Amazon, it’s like ‘hey, let’s get together and show our support and be part of the community’, which is really inspiring.”

As a self-proclaimed ally, she can relate to the LGBTQIA+ community. “Growing up in Canada as a Chinese Canadian, I know how it feels to be to be left out and stigmatized and not feel like you're part of the group, or welcome. So I can imagine how other groups of people feel, even if I don’t have full visibility into all the problems and discrimination that they face. I think it’s important to stand up for what I think is right and not just have those values and keep it to myself.”

In light of recent events, she’s been impressed by the top-down communication at Amazon, from vice president to director level, with each leader taking the time to listen to employees and expressing their views that what’s happening to Black people in the U.S. isn’t right.

“We need to make the workplace more human than it is right now. We spend eight hours a day here, and we make friends. It’s also about keeping that diversity in hiring, which I think is one of the best ways to break down barriers, by having cross-community, cross-culture, cross-gender friendships and communications.”

Mentoring is another way Jiang promotes diversity and inclusion. “I’m what they call ‘women in tech’, and I’ve been in my career for about six years, so I think it’s important to mentor other women and girls, so they don’t feel left out or scared.”

Luyolo Magangane, applied scientist, Amazon Elastic Compute Cloud (EC2)

Located in South Africa, Luyolo Magangane (pronouns: he/him) joined Amazon just over a year ago, after a friend referred him for a machine learning role.

Luyolo Magangane, applied scientist, Amazon Elastic Compute Cloud (EC2)
Luyolo Magangane, applied scientist, Amazon Elastic Compute Cloud (EC2)

“I’m in the placement team, and we try to help customers have the best experience possible whenever they use AWS. So if a customer launches an EC2 instance, my team is in charge of the decision-making algorithm that chooses where to place that instance,” he explains.

Prior to Amazon, he studied electrical and computer engineering at the University of Cape Town and obtained a master’s degree in artificial intelligence at Stellenbosch University. He had a few jobs within the industry before joining Amazon.

He’s a member of Amazon’s glamazon affinity group, where he identifies as an ally and believes it’s important that others do too.

“Everyone should believe in the respect of the humanity of people first. When you meet someone, you have no context of their background or how they grew up. The only thing you know is that you are human, and they're also human. Your sexual orientation, gender identity, or racial identity doesn’t matter. It becomes much harder to be bigoted and to oppress someone if everyone starts from that perspective,” he says.

Magangane believes his support for the LGBTQIA+ community stems from his childhood, during which South Africa saw the end of apartheid, a system of institutionalized racial segregation from 1948 until the early 1990s.

“That was when [Nelson] Mandela was released from prison. That was when you could see the tides of change coming, from minority rule to democracy, which was incredible,” he explains.

“Every day I was encouraged to dream. And so, the benefit of being born in an environment like that led to me being born very free of prejudice. But because, historically, I come from a somewhat conservative background, I have a lot of friends and family who I care about who aren't as open minded as I think they could be.”

When he thinks about Pride and the Black Lives Matter movement and what society can learn from these events, he quotes Killer Mike, an American rapper, songwriter, actor, and activist: “It’s to ‘strategize, organize, and mobilize’, peaceful protests. It’s always done through people organizing, coming out, being peaceful, and saying that we believe what's happened is wrong and things need to change,” he says.

“I think part of that is not tolerating bigotry, which is one of the challenges you have to deal with in the Black community. You’re taught to pick and choose your battles, but you end up tolerating all those things that you don't battle, which only encourages it. You have to look bigotry in the eye and demand change. You cannot tolerate any of that. Even if institutions have to change, we’re demanding the change now.”

Shane McGarry, data scientist, Amazon Fashion

Shane McGarry (pronouns: they/them) joined Amazon earlier this year as a data scientist, focused on improving the company’s fashion catalogue using machine learning and other techniques “to create a stellar experience for our customers.”

Shane McGarry, data scientist, Amazon Fashion
Shane McGarry, data scientist, Amazon Fashion

McGarry, who identifies as non-binary, meaning they (McGarry prefers the pronouns they/them to he/she, thus the use of their, they, and them in this section) don’t exclusively identify as a man or a woman, recently earned their PhD in computer science from Maynooth University, about 25 minutes outside Dublin, Ireland, where their thesis work focused on improving the search experience within digital research environments (historical records, etc.) through visual search techniques.

Before joining Amazon, McGarry held several software development roles, where they encountered challenges.

“I’m non-binary, and I’m not traditionally masculine in any way shape or form, from my speech patterns to the way I carry myself,” McGarry explains. “What I found is that I was often ignored in ways that my colleagues with the same level of experience weren’t. When working with clients, if I dealt with them over email, they were receptive to my ideas, but when we started talking over the phone and they would hear my voice, suddenly they would become skeptical of what I was saying.”

McGarry says they encountered similar challenges with management.

“There were a lot of times when my opinion was brushed to the side, despite being proven consistently right. I would say ‘I see a problem; I think we should do this differently.’ They would ignore me, and no matter how many times I was proven right, I was never taken seriously.”

Affinity groups and diversity at Amazon

After joining Amazon, McGarry became involved in glamazon, one of 12 affinity groups within the company aimed at bringing employees together across businesses and locations around the globe. They’ve been impressed with glamazon and with their organization’s response to recent events related to the killing of George Floyd and how it’s recognizing Pride Month.

“The management within Amazon Fashion has really impressed me, especially within the past few weeks with everything that’s been occurring. …The president of our business had an all-hands meeting where she invited a global diversity and inclusion leader who has dealt with racial trauma. She talked to us about racial trauma, what it is, and how it affects people.”

Asked about lessons we can derive from recent current events, McGarry says, “In terms of the Black Lives Matter movement, it’s really important for us as individuals, as well as the company as a whole, to examine our racial biases that result from growing up in a culture that favors white people. Having a racial bias doesn’t make you a bad person. But refusing to acknowledge it, to examine it, and to work towards unlearning it, that’s where the problem lies.”

McGarry, who grew up in northeast Ohio within a deeply religious family, understands firsthand the challenges of dealing with bias and prejudice. For McGarry, Pride Month represents an opportunity to celebrate who they are without fear.

“As someone who grew up in the eighties and nineties in a deeply religious home where being gay wasn’t acceptable, and hearing messages from the community and church that gay people are evil, that God hates them, you get inundated with all of these negative messages, and you really begin to hate yourself, who you are, and you live in constant fear. So for me, Pride Month is about letting a lot of that go and celebrating yourself for who you are and really embracing it. At the same time, we have to remember our history, how far we’ve come, but yet how far we still need to go.”

Read more stories like this in our Working at Amazon section, or take a look at some of our available career opportunities in science.

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We're building systems that turn research into real-world impact — developing AI-driven detection systems that identify and remediate security access violations across Amazon's global operations, and building ML solutions that leverage product images, text, and tabular data to improve safety and compliance mechanisms across Amazon's entire product catalog. If this sounds interesting to you then we have a range of opportunities for you to explore. We're looking for PhD students across multiple research domains to invent, design, and implement state-of-the-art solutions for never-before-solved problems. Your work here won't just stay in a notebook — it ships to production and reaches customers worldwide. Check out the details below including the job responsibilities, team details, and basic qualifications before submitting your application. You can find more information about the Amazon Science community as well as interview preparation tips via the links below; - https://www.amazon.science/ - https://amazon.jobs/content/en/career-programs/university/science - https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You'll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon's customer focused culture. The ideal intern should have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life You'll spend your first weeks scoping your project with your mentor, then own the research and implementation end-to-end. Your work could involve building graph-based ML models and knowledge graphs that detect and remediate access violations at global scale, developing behavioral pattern clustering and automated reasoning systems for security operations, or researching multimodal and computer vision approaches on product catalog data to improve safety and compliance mechanisms — depending on the team you're matched with. Many interns publish at top-tier conferences or see their work deployed to production before the internship ends. Interns may also be considered for a return offer at the end of their internship, subject to performance evaluation and headcount availability. Further benefits of an Amazon Science internship include; - All of our internships offer a competitive salary - Interns are paired with an experienced manager and mentor(s) - Interns get invited to different intern program or office events - Interns can build their professional and personal network with other Amazon Scientists - Interns can potentially publish work at top tier conferences About the team We generally hire interns for multiple teams in Romania, including but not limited to; • CoSS — Research and develop ML solutions that improve safety and compliance across Amazon's entire product catalog working with tabular, textual, and product image data using deep learning, computer vision, LLMs, and multimodal models • Monitored Access Detection — Build AI-driven detection and remediation systems that identify global access violations across Amazon — leveraging knowledge graphs, graph modeling, behavioral pattern clustering, generative AI, and reinforcement learning to create a self-improving, closed-loop security system. You'll submit a single application and we'll match you with science teams best aligned with your research interests. Applications are reviewed on a rolling basis, and your application stays active until we find a team match or confirm there are no matches available. Start dates are available throughout the year for durations of between 3–6 months. Please note, each team has different start date and duration preferences — your recruiter will confirm the preferences of the team you're matched with prior to interviewing. We offer science internships in multiple locations across the EMEA region and you can indicate your interest in all these locations by applying here (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, South Africa, Spain, Sweden, UAE, and UK). Please note we do not offer remote internships.
IL, Tel Aviv
We're building systems that turn research into real-world impact — powering sports experiences for millions of Prime Video customers, pioneering multimodal document intelligence, building autonomous AI agents that reason, plan, and act, and transforming how customers discover products they love. If this sounds interesting to you then we have a range of opportunities for you to explore. We're looking for Masters students across multiple research domains to invent, design, and implement state-of-the-art solutions for never-before-solved problems. Your work here won't just stay in a notebook — it ships to production and reaches customers worldwide. Check out the details below including the job responsibilities, team details, and basic qualifications before submitting your application. You can find more information about the Amazon Science community as well as interview preparation tips via the links below; - https://www.amazon.science/ - https://amazon.jobs/content/en/career-programs/university/science - https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You'll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon's customer focused culture. The ideal intern should have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life You'll spend your first weeks scoping your project with your mentor, then own the research and implementation end-to-end. Your work could involve building computer vision models that power live sports experiences for Prime Video, developing multimodal GenAI solutions for AWS document intelligence, creating agentic AI systems that reason and act autonomously, or advancing recommendation models that transform how customers discover content — depending on the team you're matched with. Many interns publish at top-tier conferences or see their work deployed to production before the internship ends. Interns may also be considered for a return offer at the end of their internship, subject to performance evaluation and headcount availability. Further benefits of an Amazon Science internship include; - All of our internships offer a competitive salary - Interns are paired with an experienced manager and mentor(s) - Interns get invited to different intern program or office events - Interns can build their professional and personal network with other Amazon Scientists About the team We're hiring interns for multiple teams in Israel, including but not limited to; • Prime Video Sports — Build innovative sports experiences for Prime Video, spanning computer vision, 3D simulation, and personalized content recommendations. • Personalization — Leverage LLMs, NLP, and recommender systems to match customers with products that align with their passions and shopping preferences. • Agentic AI — Build next-generation agentic AI systems that automate real-world knowledge work, spanning retrieval-augmented generation, multi-agent workflows, long-term memory and personalization, knowledge-graph construction, and agent evaluation. • DS3 Textract — Develop multimodal generative AI algorithms that pioneer state-of-the-art document understanding solutions impacting millions of customers. You'll submit a single application and we'll match you with science teams best aligned with your research interests. Applications are reviewed on a rolling basis, and your application stays active until we find a team match or confirm there are no matches available. Start dates are available throughout the year. Some teams offer full-time internships (3–6 months) while others offer part-time positions (50–60%, 8–12 months) — your recruiter will confirm the format during team matching. We offer science internships in multiple locations across the EMEA region and you can indicate your interest in all these locations by applying here (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, South Africa, Spain, Sweden, UAE, and UK). Please note we do not offer remote internships.
US, VA, Arlington
WW Installments is one of the fastest growing businesses within Amazon and we are looking for an Applied Scientist to join the team. This group has been entrusted with a massive charter that will impact every customer that visits Amazon.com. We are building the next generation of features and payment products that maximize customer enablement in a simple, transparent, and customer obsessed way. Through these products, we will deliver value directly to Amazon customers improving the shopping experience for hundreds of millions of customers worldwide. Our mission is to delight our customers by building payment experiences and financial services that are trusted, valued, and easy to use from anywhere in any way. As an Applied Scientist within WW Installments, you will be responsible for building machine learning models and pipelines with direct customer impact. These models represent a core capability for WW Installments and businesses across Amazon. Your work will directly impact customers by influencing how they interact with financing options to make purchases. You will work across functions including data engineering, software development, and business to induce data driven decisions at every level of the organization. Key job responsibilities This role will be responsible for: • Developing production machine learning models and pipelines for the WW Installments Fraud Detection team that directly impact customers. • Apply expertise in machine learning to develop large-scale production systems that are deployed across Amazon businesses. • Identify business opportunities, define and execute modeling approach, then deliver outcomes to various Amazon businesses with an Amazon-wide perspective for solutions. • Lead the implementation of production ML from a scientific perspective including identifying consumer financial credit and fraud risks, key milestones, and paths to mitigate risks. • Identifying new opportunities to influence business strategy and product vision using data science and machine learning. • Continually improve the WW Installments ML roadmap automating and simplifying whenever possible. • Coordinate support across engineers, scientists, and stakeholders to deliver ML pipelines, analytics projects, and build proof of concept applications. • Work through significant business and technical ambiguity delivering on analytics roadmap across the team with autonomy.
US, WA, Seattle
Application deadline: Oct 27, 2026 The AWS Data Center Services team is hiring a Principal Applied Scientist to innovate and advance the science behind solutions to problems in the rapidly growing AWS data center space. These problems range from bespoke computer vision models to support our physical infrastructure functions such as repair activities, to increasing the certainty of decisions made by our generative AI service without sacrificing latency or performance. For example, when a data center technician is triaging a critical electrical event at 2am and alarms cascade in seconds, our AI service has to cross-reference topology, live readings, maintenance history, and design documents within minutes - work that today takes an order of magnitude more time and intervention from a senior engineer. As a Principal Applied Scientist, you will work backwards from these problems and partner with software development teams to deliver solutions. You will work on problems ranging from selecting, training and evolving computer vision models for targeted activities on AWS infrastructure inside our data centers; to building smart retrieval algorithms, reduce model hallucination on safety-critical outcomes, continually improve latency and performance, and ensure our generative AI service's knowledgeable stays current and the service is constantly getting smarter beyond just knowledge retrieval. A day in the life You start the morning reviewing traces from last night’s incident triage. The agent correctly walked the topology to the upstream breaker but missed a recent maintenance change that was the real cause — so you design an experiment: does feeding work-order history into the traversal improve accuracy? You test it against historical incident data. Mid-morning, you review verification traces and catch the agent missing a spec deep in a submittal. After lunch, a field engineer walks you through manually cross-referencing five systems during an incident and you turn their scenario into a new benchmark. In the afternoon, you prototype cross-discipline reasoning: when a cascade spans electrical and cooling, can the lead agent delegate scoped investigations and still hold one coherent hypothesis? You publish results and draft a paper. You own the full lifecycle — research through production deployment. About the team Data Center Services is part of AWS Infrastructure Services that owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain - and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.