Amanda Cullen, left, is seen speaking at 2017 San Diego Comic Con panel. To her right is Dr. Bo Ruberg.
Amanda Cullen, left, is seen speaking at a 2017 Comic Con panel. To her right is Dr. Bo Ruberg. Cullen, a PhD candidate in informatics at the University of California, Irvine, is interested in how to foster inclusive communities in virtual spaces. That interest brought Cullen to an internship at Twitch.
Credit: Emma Waldron Trammell

How one intern’s research had real-world impact for Twitch moderators

Amanda Cullen, a PhD candidate in informatics at the University of California, Irvine, wanted to do work that had an impact outside of academia — she found an ideal opportunity at Twitch.

Like physical communities, online gathering places can vary substantially in terms of how welcoming they feel. Amanda Cullen, a PhD candidate in informatics at the University of California, Irvine, is deeply interested in how to foster genuinely inclusive communities in virtual spaces.

“My dissertation, and my research for the past couple of years, has been about examining diversity and inclusion issues in games,” she said.

That interest brought Cullen to an internship at Twitch — a live streaming service that features gaming, esports, and other entertainment — which Amazon acquired in 2014. She worked with the Community Health team and science and analytics manager, Sanjay Kairam. She was curious about how her work might have an impact outside academia.

“I wanted to dip my toe in the waters and see what it was like to be a researcher on the industry side,” Cullen said. “I got paired up with Sanjay and was given this really incredible project thinking about Twitch moderators.”

From research to real world impact

Channel moderators weren’t an obvious focus for her at first. Cullen had come to Twitch with a dissertation looking at the experience of women on the platform as professional players and streamers, and how the challenges and opportunities of streaming might be different for them.

Sanjay Kairam Twitch.jpg
Sanjay Kairam, science and analytics manager, says Twitch’s community moderators are the “special sauce that makes the whole service work”.

But Kairam believed that Twitch’s community moderators were the “special sauce that makes the whole service work”. And he also suspected that there were gaps in the company’s knowledge about the kinds of support that might benefit them.

As Cullen discussed the focus of her research internship with Kairam, she realized the work of community moderators in fostering welcoming online spaces had been a blind spot in her dissertation, and that — by better understanding their needs and how to support them — she could push forward the overall goals of her doctoral research.  She recognized the opportunity and modified her research project at Twitch to survey and assess moderators’ needs.

Cullen started with the basics: how moderators came to the role, and how streamers would find them (every Twitch channel has the opportunity to select its own moderators). Then she got into how they worked with the channel creators, how they helped develop norms and standards for behavior within their channels, and how they actively worked to guide the community around those ideas.

Cullen was also interested in what tools moderators wanted or needed, and how they responded to both positive and negative behavior within their channels.

“That led us to think about new resources that could be created to help moderators think about their roles and feel a greater sense of community — not just within their channel, but throughout Twitch as a whole,” says Cullen.

Cullen’s findings were put to direct use at Twitch: “Amanda's work shed a lot of really detailed light on moderator needs, which has propelled us to build better tools for our moderators,” Kairam said.

This support potentially had some very positive knock-on effects for moderators.

“A lot of what Amanda's work helped to unpack was that moderators are playing different roles within a channel. It really got the team thinking about how we could fine tune the experience for different types of roles that moderators play — so that they can work more effectively in each of those roles,” Kairam said.

Cullen has enjoyed observing the impact of her research. 

“After completing my internship, I watched things change and saw announcements about new resources or products happen and thought, ‘I wonder how much I influenced that?’ I'm looking forward to seeing that continue,” she said.

Twitch as a science internship destination

While Twitch might not seem like an obvious destination for science internships, the service actually offers a variety of potential science and engineering intern opportunities.

The nature and scale of Twitch makes a lot of questions and a lot of different research areas super cutting-edge.
Sanjay Kairam

For example, Cullen’s research proved important in identifying and understanding moderator needs that could be addressed through machine learning (ML).

“We have an ML-powered tool for moderators called AutoMod,” Kairam noted, “that automatically flags messages which may be toxic and holds them for channel moderators to review. Community Health also has an ML group called Proactive Detection, which designs models to identify and prevent various types of bad behavior across Twitch.”

Kairam also noted Twitch is actively recruiting science interns across a variety of subjects.

“A lot of times, when students think about interning at tech companies, they're thinking specifically about technical projects, technical roles,” Kairam said.

There are, of course, many technical opportunities for those interested in pushing the state of the art in machine learning: by generating recommendations for live content, for example, or building natural language processing models to detect harmful chat messages. But Kairam said there’s plenty of room for science interns in a variety of disciplines, including on the Community Health team, which is focused on creator and viewer safety and support.

Find more science internships at Amazon

Explore the full list of opportunities for applied science internships on our careers page.

“There's a lot of value to bringing into product discussions social science researchers, who are able to think through a complex problem and develop a new way of thinking about it,” he said.

Looking at problems from new points of view is powerful and enables Kairam’s team to “introduce a new mental model or framework that sort of shifts the perspective and allows us to act on information that we may not have been able to act on before,” he added.

Community Health research opportunities

There’s plenty more to research within Community Health as well, including how to proactively detect bad behavior in a live context or understanding chat behavior on the giant scale of Twitch chat.

“Addressing these challenges requires a breadth of perspectives, from understanding how healthy communities form and function, to building quantitative models of chat and channel safety, to developing machine learning models that can proactively detect and remove harmful content,” Kairam said.

“The nature and scale of Twitch, in itself, makes a lot of questions and a lot of different research areas super cutting-edge,” he observed. The fact that real-world application of that research can directly impact the safety (and fun) of millions of people around the planet is valuable to academic researchers like Cullen, who want their work to help others.

Would Cullen recommend the internship to other PhDs?

“Definitely go for it,” she said. “The internship gave me more confidence in my ability to do scientific research in an industry context.”

And there’s plenty of support, no matter how long the pandemic continues to impact the office work environment. While Cullen’s internship was initially supposed to be at Twitch headquarters in San Francisco, she remained at UC Irvine. And though Cullen wasn’t meeting people face-to-face, Kairam made sure to facilitate connections with other parts of the team.

“He recognized that if I was interested in industry employment, I would want to make friends and meet people in all kinds of different areas of the company,” she said.

That helped make the experience incredibly meaningful, Cullen said. ““It ended up being a really great and valuable time for me, even from the first day.”

Doctoral candidates and others interested in pursuing an internship opportunity at Twitch, can find opportunities, and apply here.

Related content

IN, KA, Bangalore
Amazon’s Last Mile Team is looking for a passionate individual with strong optimization and analytical skills to join its Last Mile Science team in the endeavor of designing and improving the most complex planning of delivery network in the world. Last Mile builds global solutions that enable Amazon to attract an elastic supply of drivers, companies, and assets needed to deliver Amazon's and other shippers' volumes at the lowest cost and with the best customer delivery experience. Last Mile Science team owns the core decision models in the space of jurisdiction planning, delivery channel and modes network design, capacity planning for on the road and at delivery stations, routing inputs estimation and optimization. Our research has direct impact on customer experience, driver and station associate experience, Delivery Service Partner (DSP)’s success and the sustainable growth of Amazon. Optimizing the last mile delivery requires deep understanding of transportation, supply chain management, pricing strategies and forecasting. Only through innovative and strategic thinking, we will make the right capital investments in technology, assets and infrastructures that allows for long-term success. Our team members have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, scientists, and software engineers in the industry. Key job responsibilities Candidates will be responsible for developing solutions to better manage and optimize delivery capacity in the last mile network. The successful candidate should have solid research experience in one or more technical areas of Operations Research or Machine Learning. These positions will focus on identifying and analyzing opportunities to improve existing algorithms and also on optimizing the system policies across the management of external delivery service providers and internal planning strategies. They require superior logical thinkers who are able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. To support their proposals, candidates should be able to independently mine and analyze data, and be able to use any necessary programming and statistical analysis software to do so. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. As a senior scientist, you will also help coach/mentor junior scientists in the team.
US, NY, New York
Are you passionate about solving big problems from ground-up? Do you enjoy building new state-of-the-art products at internet scale? Come lead the innovation in this startup team, vertical ad products. This is a green field problem without a known answer or a pattern to follow. We have ambitious vision to simplify full funnel advertising solutions, at scale, with specialized agentic AI-powered models and diversify the demand to strategic verticals including finserv, autos, locals.. etc. We are seeking an experienced Applied Scientist to drive innovation in our Ads Foundational Model. In this individual contributor role, you will apply advanced machine learning techniques to improve advertiser performance and customer experience. Key job responsibilities As an Applied Scientist on this team, you will: 1. Develop and drive the science strategy for Ads Foundational Model (Ads-FM), aligning it with the program's objectives and overall business goals. 2. Identify high-impact opportunities within Ads-FM program and lead the ideation, planning, and execution of science initiatives to address them. 3. Build and deploy machine learning models using computer vision, natural language processing, and deep learning to evaluate and enhance ad effectiveness. 4. Develop algorithms that extract meaningful signals from image, video, and audio content to predict and improve customer engagement 5. Leverage Amazon's extensive data repository to create predictive models that generate actionable recommendations for more compelling ad creative 6. Collaborate with business leaders and cross-functional teams to implement ML-powered solutions 7. Contribute to the ML roadmap for the Ads-FM program through innovation and research.
US, WA, Seattle
This role will contribute to developing the Economics and Science products and services in the Fee domain, with specialization in supply chain systems and fees. Through the lens of economics, you will develop causal links for how Amazon, Sellers and Customers interact. You will be a key and senior scientist, advising Amazon leaders how to price our services. You will work on developing frameworks and scaleable, repeatable models supporting optimal pricing and policy in the two-sided marketplace that is central to Amazon's business. The pricing for Amazon services is complex. You will partner with science and technology teams across Amazon including Advertising, Supply Chain, Operations, Prime, Consumer Pricing, and Finance. We are looking for an experienced Principal Economist to improve our understanding of seller Economics, enhance our ability to estimate the causal impact of fees, and work with partner teams to design pricing policy changes. In this role, you will provide guidance to scientists to develop econometric models to influence our fee pricing worldwide. You will lead the development of causal models to help isolate the impact of fee and policy changes from other business actions, using experiments when possible, or observational data when not. Key job responsibilities The ideal candidate will have extensive Economics knowledge, demonstrated strength in practical and policy relevant structural econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results. They will work closely with Economists, Data / Applied Scientists, Strategy Analysts, Data Engineers, and Product leads to integrate economic insights into policy and systems production. Familiarity with systems and services that constitute seller supply chains is a plus but not required. About the team The Stores Economics and Sciences team is a central science team that supports Amazon's Retail and Supply Chain leadership. We tackle some of Amazon's most challenging economics and machine learning problems, where our mandate is to impact the business on massive scale.
US, CA, Pasadena
The Amazon Center for Quantum Computing in Pasadena, CA, is looking to hire an Applied Scientist specializing in the design of microwave components for use in cryogenic environments. Working alongside other scientists and engineers, you will design and validate hardware performing microwave signal conditioning at cryogenic temperatures for Amazon quantum processors. Working effectively within a cross-functional team environment is critical. The ideal candidate will have a proven track record of hardware development from requirements development to validation. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred 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. 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. 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 and 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. Key job responsibilities Our scientists and engineers collaborate across diverse teams and projects to offer state of the art, cost effective solutions for the signal conditioning of Amazon quantum processor systems at cryogenic temperatures. You’ll bring a passion for innovation, collaboration, and mentoring to: Solve layered technical problems across our cryogenic signal chain. Develop requirements with key system stakeholders, including quantum device, test and measurement, hardware, and theory teams. Design, implement, test, deploy, and maintain innovative solutions that meet both performance and cost metrics. Research enabling technologies necessary for Amazon reach commercial viability in quantum computing . A day in the life As you research, design, and implement cryogenic microwave signal conditioning solutions, you will also: Participate in requirements, design, and test reviews. Work cross-functionally to help drive decisions using your unique technical background and skill set. Define and maintain standards for operational excellence. Work in a high-paced, startup-like environment where you are provided the resources to innovate quickly.
US, CA, Pasadena
The Amazon Center for Quantum Computing (CQC) team is looking for a passionate, talented, and inventive Research Engineer specializing in hardware design for cryogenic environments. The ideal candidate should have expertise in 3D CAD (SolidWorks), thermal and structural FEA (Ansys/COMSOL), hardware design for cryogenic applications, design for manufacturing, and mechanical engineering principles. The candidate must have demonstrated experience driving designs through full product development cycles (requirements, conceptual design, detailed design, manufacturing, integration, and testing). Candidates must also have a strong background in both cryogenic mechanical engineering theory and implementation. Working effectively within a cross-functional team environment is critical. Key job responsibilities The CQC collaborates across teams and projects to offer state-of-the-art, cost-effective solutions for scaling the signal delivery to quantum processor systems at cryogenic temperatures. Equally important is the ability to scale the thermal performance and improve EMI mitigation of the cryogenic environment. You will work on the following: - High density novel packaging solutions for quantum processor units - Cryogenic mechanical design for novel cryogenic signal conditioning sub-assemblies - Cryogenic mechanical design for signal delivery systems - Simulation-driven designs (shielding, filtering, etc.) to reduce sources of EMI within the qubit environment. - Own end-to-end product development through requirements, design reports, design reviews, assembly/testing documentation, and final delivery A day in the life As you design and implement cryogenic hardware solutions, from requirements definition to deployment, you will also: - Participate in requirements, design, and test reviews and communicate with internal stakeholders - Work cross-functionally to help drive decisions using your unique technical background and skill set - Refine and define standards and processes for operational excellence - Work in a high-paced, startup-like environment where you are provided the resources to innovate quickly About the team The Amazon Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, on a mission to develop a fault-tolerant quantum computer. Inclusive Team Culture Here at Amazon, 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 conferences, inspire us to never stop embracing our uniqueness. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred 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. 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. Export Control Requirement Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.
IT, Turin
As an Applied Scientist in the Alexa AI team, you will spearhead the advancement and deployment of state-of-the-art ML/RAG systems that revolutionize how millions of customers interact with Alexa. You'll leverage your expertise in machine learning, natural language processing, and large language models to create reliable, scalable, high-performance products that set new standards in operational excellence. Working at the intersection of research and production, you'll translate latest AI innovations into customer-facing features that delight users daily. Your work will span the full ML lifecycle—from analyzing customer behavior patterns and building novel metrics for personal digital assistants, to deploying automated training pipelines and conducting rigorous A/B testing across diverse devices and endpoints. Collaborating closely with business, engineering, and science teams across Amazon, you'll lead high-visibility programs that automate workflows and deliver measurable customer impact. This role offers the unique opportunity to publish at top-tier conferences while seeing your innovations scale to one of the world's most popular voice assistants, serving millions of customers globally. Key job responsibilities As an Applied Scientist in the Alexa AI team: - You'll analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices and endpoints. Your work will involve creating deep learning, policy-based learning, and machine learning algorithms that directly impact customer experiences, translating complex data patterns into actionable insights that drive product innovation. - Your technical leadership will extend to building and deploying automated model training and evaluation pipelines, implementing complex machine learning and deep learning algorithms, and conducting rigorous model and data analysis through online A/B testing. You'll research and implement novel approaches that push the boundaries of what's possible in conversational AI. - Beyond model development, you'll ensure operational excellence by taking ownership of production systems, including on-call responsibilities during peak and non-peak hours. Working alongside Software Development Engineers, you'll deploy fixes and handle high-severity issues, ensuring our ML systems maintain the reliability and performance that millions of Alexa customers depend on daily. A day in the life As an Applied Scientist in the Alexa AI team, your day will involve collaborating with talented engineers and scientists to build scalable solutions for our conversational assistant. You'll dive into data analysis, experiment with novel algorithms, and iterate on models based on real-time user feedback. Working in a fast-paced, ambiguous environment, you'll tackle complex technical challenges—from debugging production issues to presenting research findings to stakeholders. Your self-motivated approach will drive you to swiftly deliver impactful solutions while maintaining the high standards that define our mission to revolutionize user experiences for millions of customers. About the team The Alexa AI team develops the intelligence behind one of the world's most popular voice assistants, serving millions of customers globally. We're a diverse group of scientists, engineers, and researchers united by our mission to make Alexa more natural, helpful, and delightful. Our culture thrives on innovation, collaboration, and customer obsession. We tackle some of the most challenging problems in conversational AI—from natural language understanding to personalization at scale. Here, you'll work alongside world-class talent, publish at top-tier conferences, and see your innovations impact customers daily. We move fast, think big, and celebrate both successes and learnings.
IT, Turin
As an Applied Scientist in the Alexa AI team, you will spearhead the advancement and deployment of state-of-the-art ML/RAG systems that revolutionize how millions of customers interact with Alexa. You'll leverage your expertise in machine learning, natural language processing, and large language models to create reliable, scalable, high-performance products that set new standards in operational excellence. Working at the intersection of research and production, you'll translate latest AI innovations into customer-facing features that delight users daily. Your work will span the full ML lifecycle—from analyzing customer behavior patterns and building novel metrics for personal digital assistants, to deploying automated training pipelines and conducting rigorous A/B testing across diverse devices and endpoints. Collaborating closely with business, engineering, and science teams across Amazon, you'll lead high-visibility programs that automate workflows and deliver measurable customer impact. This role offers the unique opportunity to publish at top-tier conferences while seeing your innovations scale to one of the world's most popular voice assistants, serving millions of customers globally. Key job responsibilities As an Applied Scientist in the Alexa AI team: - You'll analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices and endpoints. Your work will involve creating deep learning, policy-based learning, and machine learning algorithms that directly impact customer experiences, translating complex data patterns into actionable insights that drive product innovation. - Your technical leadership will extend to building and deploying automated model training and evaluation pipelines, implementing complex machine learning and deep learning algorithms, and conducting rigorous model and data analysis through online A/B testing. You'll research and implement novel approaches that push the boundaries of what's possible in conversational AI. - Beyond model development, you'll ensure operational excellence by taking ownership of production systems, including on-call responsibilities during peak and non-peak hours. Working alongside Software Development Engineers, you'll deploy fixes and handle high-severity issues, ensuring our ML systems maintain the reliability and performance that millions of Alexa customers depend on daily. A day in the life As an Applied Scientist in the Alexa AI team, your day will involve collaborating with talented engineers and scientists to build scalable solutions for our conversational assistant. You'll dive into data analysis, experiment with novel algorithms, and iterate on models based on real-time user feedback. Working in a fast-paced, ambiguous environment, you'll tackle complex technical challenges—from debugging production issues to presenting research findings to stakeholders. Your self-motivated approach will drive you to swiftly deliver impactful solutions while maintaining the high standards that define our mission to revolutionize user experiences for millions of customers. About the team The Alexa AI team develops the intelligence behind one of the world's most popular voice assistants, serving millions of customers globally. We're a diverse group of scientists, engineers, and researchers united by our mission to make Alexa more natural, helpful, and delightful. Our culture thrives on innovation, collaboration, and customer obsession. We tackle some of the most challenging problems in conversational AI—from natural language understanding to personalization at scale. Here, you'll work alongside world-class talent, publish at top-tier conferences, and see your innovations impact customers daily. We move fast, think big, and celebrate both successes and learnings.
IT, Turin
As an Applied Scientist in the Alexa AI team, you will spearhead the advancement and deployment of state-of-the-art ML/RAG systems that revolutionize how millions of customers interact with Alexa. You'll leverage your expertise in machine learning, natural language processing, and large language models to create reliable, scalable, high-performance products that set new standards in operational excellence. Working at the intersection of research and production, you'll translate latest AI innovations into customer-facing features that delight users daily. Your work will span the full ML lifecycle—from analyzing customer behavior patterns and building novel metrics for personal digital assistants, to deploying automated training pipelines and conducting rigorous A/B testing across diverse devices and endpoints. Collaborating closely with business, engineering, and science teams across Amazon, you'll lead high-visibility programs that automate workflows and deliver measurable customer impact. This role offers the unique opportunity to publish at top-tier conferences while seeing your innovations scale to one of the world's most popular voice assistants, serving millions of customers globally. Key job responsibilities As an Applied Scientist in the Alexa AI team: - You'll analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices and endpoints. Your work will involve creating deep learning, policy-based learning, and machine learning algorithms that directly impact customer experiences, translating complex data patterns into actionable insights that drive product innovation. - Your technical leadership will extend to building and deploying automated model training and evaluation pipelines, implementing complex machine learning and deep learning algorithms, and conducting rigorous model and data analysis through online A/B testing. You'll research and implement novel approaches that push the boundaries of what's possible in conversational AI. - Beyond model development, you'll ensure operational excellence by taking ownership of production systems, including on-call responsibilities during peak and non-peak hours. Working alongside Software Development Engineers, you'll deploy fixes and handle high-severity issues, ensuring our ML systems maintain the reliability and performance that millions of Alexa customers depend on daily. A day in the life As an Applied Scientist in the Alexa AI team, your day will involve collaborating with talented engineers and scientists to build scalable solutions for our conversational assistant. You'll dive into data analysis, experiment with novel algorithms, and iterate on models based on real-time user feedback. Working in a fast-paced, ambiguous environment, you'll tackle complex technical challenges—from debugging production issues to presenting research findings to stakeholders. Your self-motivated approach will drive you to swiftly deliver impactful solutions while maintaining the high standards that define our mission to revolutionize user experiences for millions of customers. About the team The Alexa AI team develops the intelligence behind one of the world's most popular voice assistants, serving millions of customers globally. We're a diverse group of scientists, engineers, and researchers united by our mission to make Alexa more natural, helpful, and delightful. Our culture thrives on innovation, collaboration, and customer obsession. We tackle some of the most challenging problems in conversational AI—from natural language understanding to personalization at scale. Here, you'll work alongside world-class talent, publish at top-tier conferences, and see your innovations impact customers daily. We move fast, think big, and celebrate both successes and learnings.
IT, Turin
As an Applied Scientist in the Alexa AI team, you will spearhead the advancement and deployment of state-of-the-art ML/RAG systems that revolutionize how millions of customers interact with Alexa. You'll leverage your expertise in machine learning, natural language processing, and large language models to create reliable, scalable, high-performance products that set new standards in operational excellence. Working at the intersection of research and production, you'll translate latest AI innovations into customer-facing features that delight users daily. Your work will span the full ML lifecycle—from analyzing customer behavior patterns and building novel metrics for personal digital assistants, to deploying automated training pipelines and conducting rigorous A/B testing across diverse devices and endpoints. Collaborating closely with business, engineering, and science teams across Amazon, you'll lead high-visibility programs that automate workflows and deliver measurable customer impact. This role offers the unique opportunity to publish at top-tier conferences while seeing your innovations scale to one of the world's most popular voice assistants, serving millions of customers globally. Key job responsibilities As an Applied Scientist in the Alexa AI team: - You'll analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices and endpoints. Your work will involve creating deep learning, policy-based learning, and machine learning algorithms that directly impact customer experiences, translating complex data patterns into actionable insights that drive product innovation. - Your technical leadership will extend to building and deploying automated model training and evaluation pipelines, implementing complex machine learning and deep learning algorithms, and conducting rigorous model and data analysis through online A/B testing. You'll research and implement novel approaches that push the boundaries of what's possible in conversational AI. - Beyond model development, you'll ensure operational excellence by taking ownership of production systems, including on-call responsibilities during peak and non-peak hours. Working alongside Software Development Engineers, you'll deploy fixes and handle high-severity issues, ensuring our ML systems maintain the reliability and performance that millions of Alexa customers depend on daily. A day in the life As an Applied Scientist in the Alexa AI team, your day will involve collaborating with talented engineers and scientists to build scalable solutions for our conversational assistant. You'll dive into data analysis, experiment with novel algorithms, and iterate on models based on real-time user feedback. Working in a fast-paced, ambiguous environment, you'll tackle complex technical challenges—from debugging production issues to presenting research findings to stakeholders. Your self-motivated approach will drive you to swiftly deliver impactful solutions while maintaining the high standards that define our mission to revolutionize user experiences for millions of customers. About the team The Alexa AI team develops the intelligence behind one of the world's most popular voice assistants, serving millions of customers globally. We're a diverse group of scientists, engineers, and researchers united by our mission to make Alexa more natural, helpful, and delightful. Our culture thrives on innovation, collaboration, and customer obsession. We tackle some of the most challenging problems in conversational AI—from natural language understanding to personalization at scale. Here, you'll work alongside world-class talent, publish at top-tier conferences, and see your innovations impact customers daily. We move fast, think big, and celebrate both successes and learnings.
US, NY, New York
We are seeking a Human-Robot Interaction (HRI) Applied Scientist to develop cutting-edge interactions that make robots feel alive, personal, and fun. In this role, you will focus on verbal and non-verbal conversational systems, social dynamics, memory, and long-term relationship formation between robots, their environments, and the people they interact with. Your contributions will be essential in advancing robotics by enabling expressive, socially intelligent, and trustworthy interactions between robots and humans. Key job responsibilities - Develop interactive systems that leverage large language models, multimodal inputs and outputs, reinforcement learning from human feedback, or other advanced techniques to achieve fluid, engaging, and socially appropriate robot behavior - Design and implement intelligent conversational systems that handle turn-taking, grounding, interruption, and incorporates context drawn from a robot's physical environment and shared history with a user - Integrate perceptual sensor streams including gaze, facial expression, gesture, posture, and more to understand social context and produce coherent, lifelike interactions. - Develop memory and personalization systems that allow robots to form lasting relationships with individual users, learn their environments, and adapt their behavior over weeks and months - Stay updated on advancements in HRI, NLP, multimodal AI, and cognitive and social science to apply cutting-edge techniques to robot interaction challenges - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers - Bridge research initiatives with practical engineering implementation