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, Bengaluru
RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will independently file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.
IN, KA, Bengaluru
Selection Monitoring team is responsible for making the biggest catalog on the planet even bigger. In order to drive expansion of the Amazon catalog, we develop advanced ML/AI technologies to process billions of products and algorithmically find products not already sold on Amazon. We work with structured, semi-structured and Visually Rich Documents using deep learning, NLP and image processing. The role demands a high-performing and flexible candidate who can take responsibility for success of the system and drive solutions from research, prototype, design, coding and deployment. We are looking for Applied Scientists to tackle challenging problems in the areas of Information Extraction, Efficient crawling at internet scale, developing ML models for website comprehension and agents to take multi-step decisions. You should have depth and breadth of knowledge in text mining, information extraction from Visually Rich Documents, semi structured data (HTML) and advanced machine learning. You should also have programming and design skills to manipulate Semi-Structured and unstructured data and systems that work at internet scale. You will encounter many challenges, including: - Scale (build models to handle billions of pages), - Accuracy (requirements for precision and recall) - Speed (generate predictions for millions of new or changed pages with low latency) - Diversity (models need to work across different languages, market places and data sources) You will help us to - Build a scalable system which can algorithmically extract information from world wide web. - Intelligently cluster web pages, segment and classify regions, extract relevant information and structure the data available on semi-structured web. - Build systems that will use existing Knowledge Base to perform open information extraction at scale from visually rich documents. Key job responsibilities - Use AI, NLP and advances in LLMs/SLMs and agentic systems to create scalable solutions for business problems. - Efficiently Crawl web, Automate extraction of relevant information from large amounts of Visually Rich Documents and optimize key processes. - Design, develop, evaluate and deploy, innovative and highly scalable ML models, esp. leveraging latest advances in RL-based fine tuning methods like DPO, GRPO etc. - Work closely with software engineering teams to drive real-time model implementations. - Establish scalable, efficient, automated processes for large scale model development, model validation and model maintenance. - Lead projects and mentor other scientists, engineers in the use of ML techniques. - Publish innovation in research forums.
US, CA, Santa Clara
We are seeking an Applied Scientist II to join Amazon Customer Service's Science team, where you will build AI-based automated customer service solutions using state-of-the-art techniques in retrieval-augmented generation (RAG), agentic AI, and post-training of large language models. You will work at the intersection of research and production, developing intelligent systems that directly impact millions of customers while collaborating with scientists, engineers, and product managers in a fast-paced, innovative environment. Key job responsibilities - Design, develop, and deploy information retrieval systems and RAG pipelines using embedding models, reranking algorithms, and generative models to improve customer service automation - Conduct post-training of large language models using techniques such as Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and Group Relative Policy Optimization (GRPO) to optimize model performance for customer service tasks - Build and curate high-quality datasets for model training and evaluation, ensuring data quality and relevance for customer service applications - Design and implement comprehensive evaluation frameworks, including data curation, metrics development, and methods such as LLM-as-a-judge to assess model performance - Develop AI agents for automated customer service, understanding their advantages and common pitfalls, and implementing solutions that balance automation with customer satisfaction - Independently perform research and development with minimal guidance, staying current with the latest advances in machine learning and AI - Collaborate with cross-functional teams including engineering, product management, and operations to translate research into production systems - Publish findings and contribute to the broader scientific community through papers, patents, and open-source contributions - Monitor and improve deployed models based on real-world performance metrics and customer feedback A day in the life As an Applied Scientist II, you will start your day reviewing metrics from deployed models and identifying opportunities for improvement. You might spend your morning experimenting with new post-training techniques to improve model accuracy, then collaborate with engineers to integrate your latest model into production systems. You will participate in design reviews, share your findings with the team, and mentor junior scientists. You will balance research exploration with practical implementation, always keeping the customer experience at the forefront of your work. You will have the autonomy to drive your own research agenda while contributing to team goals and deliverables. About the team The Amazon Customer Service Science team is dedicated to revolutionizing customer support through advanced AI and machine learning. We are a diverse group of scientists and engineers working on some of the most challenging problems in natural language understanding and AI automation. Our team values innovation, collaboration, and a customer-obsessed mindset. We encourage experimentation, celebrate learning from failures, and are committed to maintaining Amazon's high bar for scientific rigor and operational excellence. You will have access to world-class computing resources, massive datasets, and the opportunity to work alongside some of the brightest minds in AI and machine learning.
US, MA, N.reading
Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities - Design and implement whole body control methods for balance, locomotion, and dexterous manipulation - Utilize state-of-the-art in methods in learned and model-based control - Create robust and safe behaviors for different terrains and tasks - Implement real-time controllers with stability guarantees - Collaborate effectively with multi-disciplinary teams to co-design hardware and algorithms for loco-manipulation - Mentor junior engineer and scientists
US, CA, Sunnyvale
Amazon's AGI Information is seeking an exceptional Applied Scientist to drive science advancements in the Amazon Knowledge Graph team (AKG). AKG is re-inventing knowledge graphs for the LLM era, optimizing for LLM grounding. At the same time, AKG is innovating to utilize LLMs in the knowledge graph construction pipelines to overcome obstacles that traditional technologies could not overcome. As a member of the AKG IR team, you will have the opportunity to work on interesting problems with immediate customer impact. The team is addressing challenges in web-scale knowledge mining, fact verification, multilingual information retrieval, and agent memory operating over Graphs. You will also have the opportunity to work with scientists working on the other challenges, and with the engineering teams that deliver the science advancements to our customers. A successful candidate has a strong machine learning and agent background, is a master of state-of-the-art techniques, has a strong publication record, has a desire to push the envelope in one or more of the above areas, and has a track record of delivering to customers. The ideal candidate enjoys operating in dynamic environments, is self-motivated to take on new challenges, and enjoys working with customers, stakeholders, and engineering teams to deliver big customer impact, shipping solutions via rapid experimentation and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems. You will collaborate with applied scientists and engineers to develop novel algorithms and modeling techniques to build the knowledge graph that delivers fresh factual knowledge to our customers, and that automates the knowledge graph construction pipelines to scale to many billions of facts. Your first responsibility will be to solve entity resolution to enable conflating facts from multiple sources into a single graph entity for each real world entity. You will develop generic solutions that work fo all classes of data in AKG (e.g., people, places, movies, etc.), that cope with sparse, noisy data, that scale to hundreds of millions of entities, and that can handle streaming data. You will define a roadmap to make progress incrementally and you will insist on scientific rigor, leading by example.
US, CA, Sunnyvale
Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine innovative AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. We leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of robotics foundation models that: - Enable unprecedented generalization across diverse tasks - Integrate multi-modal learning capabilities (visual, tactile, linguistic) - Accelerate skill acquisition through demonstration learning - Enhance robotic perception and environmental understanding - Streamline development processes through reusable capabilities The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. As a Senior Applied Scientist, you will develop and improve machine learning systems that help robots perceive, reason, and act in real-world environments. You will leverage state-of-the-art models (open source and internal research), evaluate them on representative tasks, and adapt/optimize them to meet robustness, safety, and performance needs. You will invent new algorithms where gaps exist. You’ll collaborate closely with research, controls, hardware, and product-facing teams, and your outputs will be used by downstream teams to further customize and deploy on specific robot embodiments. Key job responsibilities As a Senior Applied Scientist in the Foundations Model team, you will: - Leverage state-of-the-art models for targeted tasks, environments, and robot embodiments through fine-tuning and optimization. - Execute rapid, rigorous experimentation with reproducible results and solid engineering practices, closing the gap between sim and real environments. - Build and run capability evaluations/benchmarks to clearly profile performance, generalization, and failure modes. - Contribute to the data and training workflow: collection/curation, dataset quality/provenance, and repeatable training recipes. - Write clean, maintainable, well commented and documented code, contribute to training infrastructure, create tools for model evaluation and testing, and implement necessary APIs - Stay current with latest developments in foundation models and robotics, assist in literature reviews and research documentation, prepare technical reports and presentations, and contribute to research discussions and brainstorming sessions. - Work closely with senior scientists, engineers, and leaders across multiple teams, participate in knowledge sharing, support integration efforts with robotics hardware teams, and help document best practices and methodologies.
JP, 13, Tokyo
Amazon.com strives to be Earth's most customer-centric company where people can find and discover anything they want to buy. We hire the world's brightest minds and offer them a fast-paced, technologically sophisticated, and collaborative work environment. We are seeking a talented, customer-focused Economist to join our JCI Measurement and Optimization Science Team (JCI MOST). In this role, you will design experiments and build econometric models to measure intervention impacts and deliver data-driven insights that inform leadership decisions. Amazon Economists leverage our world-class data systems to build sophisticated econometric models, drawing from diverse methodological approaches including econometric theory, empirical IO, empirical health, labor, and public economics—all highly valued skillsets at Amazon. You will work in a fast-moving environment solving critical business problems as part of cross-functional teams embedded within business units or our central science and economics organization. This role requires exceptional Causal Inference expertise, strong cross-functional collaboration skills, business acumen, and an entrepreneurial spirit to drive measurable improvements in our pricing quality and business outcomes.
CN, 31, Shanghai
As a Sr. Applied Scientist, you will be responsible for bringing new product designs through to manufacturing. You will work closely with multi-disciplinary groups including Product Design, Industrial Design, Hardware Engineering, and Operations, to drive key aspects of engineering of consumer electronics products. In this role, you will use expertise in physical sciences, theoretical, numerical or empirical techniques to create scalable models representing response of physical systems or devices, including: * Applying domain scientific expertise towards developing innovative analysis and tests to study viability of new materials, designs or processes * Working closely with engineering teams to drive validation, optimization and implementation of hardware design or software algorithmic solutions to improve product and customer risks * Establishing scalable, efficient, automated processes to handle large scale design and data analysis * Conducting research into use conditions, materials and analysis techniques * Tracking general business activity including device health in field and providing clear, compelling reports to management on a regular basis * Developing, implementing guidelines to continually optimize design processes * Using simulation tools like LS-DYNA, and Abaqus for analysis and optimization of product design * Using of programming languages like Python and Matlab for analytical/statistical analyses and automation * Demonstrating strong understanding across multiple physical science domains, e.g. structural, thermal, fluid dynamics, and materials * Developing, analyzing and testing structural solutions from concept design, feature development, product architecture, through system validation * Supporting product development and optimization through application of analysis and testing of complex electronic assemblies using advanced simulation and experimentation tools and techniques
US, WA, Redmond
Amazon Leo is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband connectivity to unserved and underserved communities around the world. As a Communications Engineer in Modeling and Simulation, this role is primarily responsible for the developing and analyzing high level system resource allocation techniques for links to ensure optimal system and network performance from the capacity, coverage, power consumption, and availability point of view. Be part of the team defining the overall communication system and architecture of Amazon Leo’s broadband wireless network. This is a unique opportunity to innovate and define novel wireless technology with few legacy constraints. The team develops and designs the communication system of Leo and analyzes its overall system level performance, such as overall throughput, latency, system availability, packet loss, etc., as well as compatibility for both connectivity and interference mitigation with other space and terrestrial systems. This role in particular will be responsible for 1) evaluating complex multi-disciplinary trades involving RF bandwidth and network resource allocation to customers, 2) understanding and designing around hardware/software capabilities and constraints to support a dynamic network topology, 3) developing heuristic or solver-based algorithms to continuously improve and efficiently use available resources, 4) demonstrating their viability through detailed modeling and simulation, 5) working with operational teams to ensure they are implemented. This role will be part of a team developing the necessary simulation tools, with particular emphasis on coverage, capacity, latency and availability, considering the yearly growth of the satellite constellation and terrestrial network. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be 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. Key job responsibilities • Work within a project team and take the responsibility for the Leo's overall communication system design and architecture • Extend existing code/tools and create simulation models representative of the target system, primarily in MATLAB • Design interconnection strategies between fronthaul and backhaul nodes. Analyze link availability, investigate link outages, and optimize algorithms to study and maximize network performance • Use RF and optical link budgets with orbital constellation dynamics to model time-varying system capacity • Conduct trade-off analysis to benefit customer experience and optimization of resources (costs, power, spectrum), including optimization of satellite constellation design and link selection • Work closely with implementation teams to simulate expected system level performance and provide quick feedback on potential improvements • Analyze and minimize potential self-interference or interference with other communication systems • Provide visualizations, document results, and communicate them across multi-disciplinary project teams to make key architectural decisions
US, WA, Seattle
Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced electromechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. Amazon is seeking a talented and motivated Principal Applied Scientist to develop tactile sensors and guide the sensing strategy for our gripper design. The ideal candidate will have extensive experience in sensor development, analysis, testing and integration. This candidate must have the ability to work well both independently and in a multidisciplinary team setting. Key job responsibilities - Author functional requirements, design verification plans and test procedures - Develop design concepts which meet the requirements - Work with engineering team members to implement the concepts in a product design - Support product releases to manufacturing and customer deployments - Work efficiently to support aggressive schedules