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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Job summarySecurity Products group is responsible for the protection of customer and corporate data. We are connected to all parts of Amazon's business and it’s massive, worldwide service-oriented architecture. We are starting the work on a new mission critical system that will preserve and improve the trusted experience that Amazon provides to its customers. This is a greenfield initiative with plenty of opportunity for innovation in the security space through new machine learning techniques.We are seeking a talented, self-directed Applied Scientist to work on the cutting edge security technologies. You'll design and run experiments, research new algorithms, and find new ways of protecting Amazon's customer trust. Besides theoretical analysis and innovation, you will work closely with talented engineers to put your algorithms and models into practice. You should thrive in ambiguous environments that require to find solutions to problems that have not been solved before. You enjoy and succeed in fast paced environments where learning new concepts quickly is a must. You leverage your exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience in building large-scale distributed systems. Your strong communication skills enable you to work effectively with both business and technical partners.Key job responsibilitiesProcess and analyze large data sets using as many techniques as necessaryDeliver scalable models that can analyze large data sets efficientlyBuild mathematical models to detect and classify specific data elements with high accuracyPrototype these models by using high-level modeling languages such as Python. A software team will be working with you to transform prototypes into production.Create, enhance, and maintain technical documentation, and present to other scientists and business leaders.
US, CA, Palo Alto
Job summaryAmazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth.Our Forecasting Products team builds end-to-end solutions for publishers, advertisers and Amazon DSP. This includes data pipelines, machine learning models, large scale data structures and indexes, advertiser recommendations (bids, products) and data visualizations. We match supply (human eyeballs) and demand (advertisers interests) in thousands of audience targeting dimensions, and recommend optimal prices.As a Senior Applied Scientist, you will:· Drive applied science (machine learning) projects end-to-end ~ from ideation, analysis, prototyping, development, metrics, and monitoring.· Conduct deep analyses on massive Ad user and contextual data sets· Propose viable modelling ideas to advance optimization or efficiency, with supporting argument, data, or, preferably, preliminary results.· Invent ways to overcome technical limitations and enable new forms of analyses to drive key technical and business decisions.· Design, develop, and maintain scalable, Machine Learning models with automated training, validation, monitoring and reporting.· Stay familiar with the field and apply state-of-the-art Machine Learning techniques to our domain problems, around forecasting, bidding, allocation, and optimization.· Produce peer-reviewed scientific paper in top journals and conferences.· Present results, reports, and data insights to both technical and business leadership.· Work across teams and lead a group of talented scientists and engineers to solve problems in the domains of forecasting, auction theory, bid optimization, and user clustering.Team video - Amazon Advertising: https://youtu.be/zD_6Lzw8raEWhy you love this opportunityAmazon is investing heavily in building a world-class advertising business. We are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and break fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit. With a broad mandate to experiment and innovate.Impact and Career GrowthYou will invent new shopper and advertiser experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon. Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us
US, CA, San Diego
Job summaryAmazon Science gives you insight into the company’s approach to customer focused scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.Please visit https://www.amazon.science for more information.Do 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?Do you want to build advanced algorithmic systems that help manage safety of millions of transactions every day?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 Machine Learning group.Major responsibilities· Use statistical and machine learning techniques to create scalable risk management systems· Learning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends· Design, development and evaluation of highly innovative models for risk management· Working closely with software engineering teams to drive real-time model implementations and new feature creations· Working 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 implementation· Tracking general business activity and providing clear, compelling management reporting on a regular basis· Research and implement novel machine learning and statistical approaches
US, WA, Seattle
Job summaryAre you excited about customer-facing research and reinventing the way people think about long-held assumptions? At Amazon, we are constantly inventing and re-inventing to be the most customer-centric company in the world. To get there, we need exceptionally talented, bright, and driven people. Amazon is one of the most recognizable brand names in the world and we distribute millions of products each year to our loyal customers.Our organization leads the innovation of Amazon’s ultra-fast grocery product initiatives. Our key vision is to transform the online grocery experience and provide a wide grocery selection in order to be the primary destination to fulfill customer’s food shopping needs. We are a team of passionate tech builders who work endlessly to make life better for our customers through amazing, thoughtful, and creative new grocery shopping experiences. To succeed, we need senior technical leaders to forge a path into the future by building innovative, maintainable, and scalable systems.The ideal candidate will be responsible for quantitative data analysis, building models and prototypes for supply chain systems, and developing state-of-the-art optimization algorithms to scale. This team plays a significant role in various stages of the innovation pipeline from identifying business needs, developing new algorithms, prototyping/simulation, to implementation by working closely with colleagues in engineering, product management, operations, retail and finance.As a senior member of the research team, you will play an integral part on our Supply Chain team with the following technical and leadership responsibilities:· Interact with engineering, operations, science and business teams to develop an understanding and domain knowledge of processes, system structures, and business requirements· Apply domain knowledge and business judgment to identify opportunities and quantify the impact aligning research direction to business requirements and make the right judgment on research project prioritization· Develop scalable mathematical models to derive optimal or near-optimal solutions to existing and new supply chain challenges· Create prototypes and simulations to test devised solutions· Advocate technical solutions to business stakeholders, engineering teams, as well as executive-level decision makers· Work closely with engineers to integrate prototypes into production system· Create policy evaluation methods to track the actual performance of devised solutions in production systems, identify areas with potential for improvement and work with internal teams to improve the solution with new features· Mentor team members for their career development and growth· Present business cases and document models, analyses, and their results in order to influence important decisions
GB, London
Amazon is seeking an outstanding Data Scientist to uncover key insights on how customers engage with Prime Video. As consumers increasingly adopt on-demand video, we need to make agile decisions in order to optimize our video selection based on the content that appeals most to our customers. The Content Analytics team enables agile decision making by developing key insights into customer engagement with our service and translating these insights into large scale predictive modelling and analytics solutions.
US, WA, Seattle
Job summaryAmazon is looking for a creative Senior Applied Scientist to tackle some of the most interesting problems on the leading edge of natural language processing (NLP) and machine learning (ML) with our Alexa Artificial Intelligence (AI) team. Alexa AI aims to reinvent search and information retrieval for a voice-forward, multi-modal future. We enable customers to interact with unstructured and semi-structured content via a broad range of customer experiences including question answering, summarization, search, and multi-turn dialogues.Key job responsibilitiesIf you are looking for an opportunity to develop innovative solutions to deep technical problems having a massive customer impact, this might be the role for you! As a Senior Applied Scientist, you will work with smart, passionate colleagues in a fast-paced environment. You will develop and help deploy novel, scalable algorithms to advance the state-of-the-art in technology areas at the intersection of NLP and ML. You will keep up with relevant research in the field of NLP and publish your work in top-tier conferences. You will contribute to a multi-year research roadmap, enabling the team to focus on the right technical challenges to delight our customers.
US, NY, New York
Job summaryAmazon AI is looking for an experienced Data Scientist with abackground in the intersection of linguistics, phonetics, or NLP andstatistics/machine learning to help build industry-leading speech andlanguage processing services.As part of our AI team in Amazon Web Services, you will work alongsideapplied scientists, software engineers, and language engineers todefine data requirements for training AI services, ensure dataquality, develop suitable evaluation metrics for novel AI features andservices, and analyze systems' input/output behavior. You will be responsiblefor implementing and maintaining data analysis tools and pipelines, creatinginsightful analyses of complex production systems, and communicating resultsto scientists, product managers, and customers.Your work will directly impact millions of our customers in the formof products and services that make use of speech and languagetechnology. You will gain hands on experience with Amazon’sheterogeneous speech, text, and structured data sources, andlarge-scale computing resources to accelerate advances in spokenlanguage processing.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.
GB, Cambridge
Job summaryAmazon is looking for a creative Applied Scientist to tackle some of the most interesting problems on the leading edge of Machine Learning (ML), Natural Language Processing (NLP), and Information Retrieval (IR) with our Device Design Group (DDG). Amazon’s Device Design Group has launched revolutionary products like Echo, Fire TV, Alexa Communications, and more. Are you interested in joining the team to lead Amazon’s next innovation?The successful candidate will develop novel ML/NLP/IR/Deep Learning technologies to make Alexa smarter. They will have a true passion for working in a collaborative, cross-functional environment that encourages thinking about optimized solutions to unique problems that do not have yet a known science solution.If you are looking for an opportunity to solve deep technical problems and build innovative solutions in a fast-paced environment working within a smart and passionate team, this might be the role for you. You will develop and implement novel algorithms and modeling techniques to leverage and advance the state-of-the-art in technology areas that are found at the intersection of ML, NLP, IR, and Deep Learning. Your work will directly impact Amazon products and services that make use of speech and language technology. You will gain hands on experience with Alexa and large-scale computing resources.In this role you will:· Work collaboratively with scientists and developers to design and implement automated, scalable MT models;· Drive scalable solutions from the business, to prototyping, production testing and through engineering directly to production;· Drive best practices on the team, deal with ambiguity and competing objectives, and mentor and guide junior members to achieve their career growth potential.
US, VA, Arlington
Are you excited about building high-performance robotic systems that can perceive, learn, and act intelligently? The Robotics AI team is creating intelligent products for Amazon's supply chain, at the scale of Amazon's supply chain.The Robotics AI software team is seeking a senior scientist to help with our Robotic Perception systems. This includes building Computer Vision systems and sensor fusion to handle the most complex situations that come with large scale. It also includes end-to-end ownership of decision explanation, fault detection, monitoring, A/B testing, large scale model training, simulation, hardware integration, and more. This work spans prototypes in the lab as well as wide-deployment systems. As a Senior scientist, you will help drive where to focus our research, coaching other scientists and engineers, performing your own studies, and building algorithms for us in production.Key Responsibilities* Research vision - Where should we be focusing our efforts* Coaching - Developing the skills of other scientists and engineers* Studies - Insights from production data or ad-hoc experimentation.* Production algorithms - Models that perform the core job of driving our robots in completing their work.Inclusive Team CultureHere at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have 12 affinity groups (employee resource groups) with more than 87,000 employees across hundreds of chapters around the world. 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 reminds team members to seek diverse perspectives, learn and be curious, and earn trust.FlexibilityIt isn’t about which 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 offer flexibility and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthWe care about your career growth too. Whether your goals are to explore new technologies, take on bigger opportunities, or get to the next level, we'll help you get there. Our business is growing fast and our people will grow with it.
US, WA, Seattle
MULTIPLE POSITIONS AVAILABLEEntity: Amazon.com Services LLC, an Amazon.com CompanyTitle: Economist IIWorksite: Seattle, WAPosition Responsibilities:Work with the economists, scientists and/or senior management on key business problems faced in retail, international retail, third party merchants, search, and/or operations. Apply the frontier of economic thinking to experiment design, forecasting, program evaluation and other areas. Build econometric models using data systems. Apply economic theory to solve business problems. Own the development of economic models and manage the data analysis, modeling and experimentation necessary to estimate and validate the models, in collaboration with scientists and engineers. Develop new techniques to process large data sets, address quantitative problems, and contribute to design of automated systems. Apply tools from applied micro-econometrics (e.g. experimental design, difference-in-difference, regression discontinuity) and forecasting (essential time series models). Leverage big data tools for data extraction. Work closely with business partners to communicate the intuition, implication and detail of economic analyses/modeling and incorporate feedback. Write up and present analysis for distribution to various levels of management at Amazon.Amazon.com is an Equal Opportunity-Affirmative Action Employer - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000
US, MA, North Reading
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 that work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even image yet. 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.We seek a talented and motivated engineer to tackle broad challenges in system-level analysis. You will work in a small team to quantify system performance at scale and to expand the breadth and depth of our analysis (e.g. increase the range of software components and warehouse processes covered by our models, develop our library of key performance indicators, construct experiments that efficiently root cause emergent behaviors). You will engage with growing teams of software development and warehouse design engineers to drive evolution of the AR system and of the simulation engine that supports our work.This role is a 6 month co-op to join AR full time (40 hours/week) from January-June 2022. Come join us in North Reading, MA, or in our newly expanded innovation hub in Westborough, MA!Both campuses provide a unique opportunity for co-ops to have direct access to robotics testing labs and manufacturing facilities.
US, CA, Palo Alto
The Query Understanding team in Amazon Search connects customer queries with billions of products through a common knowledge graph. Understanding shopping mission is the key to building an intelligent shopping assistant on Amazon. We are working on many challenging science problems in NLP, Graph Mining, Common-Sense Knowledge Extraction, and Unsupervised Learning. We are solving engineering challenges such as automatic ML training and running large BERT models within milliseconds.We are looking for a senior science manager to lead our mission to lift Amazon's search engine from a text based information retrieval engine to a knowledge based shopping assistant. In this role, you will manage teams of passionate, talented, and inventive scientists, to develop industry-leading Natural Language Processing (NLP) and Data Mining algorithms, and drive them successfully to production for the benefit of amazon customers. You will identify research directions, create roadmaps for forward-looking research and communicate them to senior leadership, and work closely with engineering teams to bring research to production. You will work with teams of talented scientists, and fill the ranks by attracting the best scientists in NLP, and Data Mining, by representing Amazon Search at international science conferences. You will work with talented peers and leverage Amazon’s heterogeneous data sources and large-scale computing resources.
US, WA, Seattle
Job summaryWe are constantly making Alexa the best voice assistant in the world. Amazon’s Alexa cloud service and Echo devices are used every day, by people you know, in and about their homes. The Alexa Monetization team is hiring talented and experienced Sr. Applied Scientists to help building the next generation products for Alexa across multiple channels and domains. We are seeking an experienced, entrepreneurial, big thinker for a confidential new initiative within Alexa. You will be joining a team doing innovative work, making a direct impact to customers, showing measurable success, and building with the latest natural language processing systems. If you are holding out for an opportunity to:Make a huge impact as an individual· Be part of a team of smart and passionate professionals who will challenge you to grow every day· Solve difficult challenges using your expertise in coding elegant and practical solutions· Create applications at a massive scale used by millions of people· Work with machine learning systems to deliver real experiences, not just researchAnd you are experienced with…· Drive applied science (machine learning) projects end-to-end ~ from ideation, analysis, prototyping, development, metrics, and monitoring· Conduct deep analyses on massive user and contextual data sets· Propose viable modeling ideas to advance optimization or efficiency, with supporting argument, data, or, preferably, preliminary results· Design, develop, and maintain scalable, Machine Learning models with automated training, validation, monitoring and reporting· Stay familiar with the field and apply state-of-the-art Machine Learning techniques to NLP and related optimization problems· Produce peer-reviewed scientific paper in top journals and conferencesAnd you constantly look for opportunities to…· Innovate, simplify, reduce waste, and increase efficiencies· Use data to make decisions and validate assumptions· Automate processes otherwise performed by humans· Learn from others and help grow those around you...then we would love to chat!In 2021, we have the opportunity to build new products and features from the ground up and we are looking for strong, bias for action engineering leaders who are not afraid of taking bold bets and trying new things to improve customer experience for Alexa.As part of a new and growing team, you will be iterating on new features and products to help drive innovation and expansion. You will work on cross-functional and cross-domain opportunities; tackle challenging projects aim to accelerate experimentations in Alexa; and build out operating mechanisms and technology to enable novel customer experiences. You will be instrumental in setting the team culture, quality bar, engineering best practices, and norms. Mentoring and growing the team around you will be one of the primary ways you measure your own success. You will have the opportunity to contribute and develop deep expertise in the areas of distributed systems, machine learning, conversational technologies, user interfaces (including voice and natural user interfaces), data storage and data pipelines.This role is exciting for scientists who love to apply startup mindset to their day-to-day, enjoy working cross-functionally to master both business and technology knowledge, and are passionate about building engineering best practices. If you are looking for opportunity to learn, grow and lead, this is the position for you.
US, WA, Seattle
Job summaryWhy this job is awesome?· This is SUPER high-visibility work: Our mission is to provide consistent, accurate, and relevant delivery information to every single page on every Amazon-owned site.· MILLIONS of customers will be impacted by your contributions: The changes we make directly impact the customer experience on every Amazon site. This is a great position for someone who likes to leverage Machine learning technologies to solve the real customer problems, and also wants to see and measure their direct impact on customers.· We are a cross-functional team that owns the ENTIRE delivery experience for customers: From the business requirements to the technical systems that allow us to directly affect the on-site experience from a central service, business and technical team members are integrated so everyone is involved through the entire development process.· You will help the Delivery Experience organization to build causal inference framework and analyze the long-term effect on business· Your work will support the Amazon leadership to make visionary business decisions.· Do you want to join an innovative team of scientists and engineers who use machine learning and statistical inference techniques to deliver the best delivery experience on every Amazon-owned site?· · Are you excited by the prospect of analyzing and modeling terabytes of data on the cloud and create state-of-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 like to innovate and simplify?If yes, then you may be a great fit to join the Delivery Experience Machine Learning team.Major responsibilities:· Research and implement causal inference techniques to create scalable and effective models in Delivery Experience (DEX) systems· Solve business problems and identify business opportunities to provide the best delivery experience on all Amazon-owned sites.· Design and develop machine learning framework to measure the long-term effect of all models in DEX systems· Design and develop search ranking, recommendation and personalization models to improve Amazon customer experience· Analyze and understand large amounts of Amazon’s historical business data to detect patterns, to analyze trends and to identify correlations and causalities· Establishing scalable, efficient, automated processes for large scale data analysis and causal inference