Social
HokieTokie.png

Team HokieTokie

We are committed to advancing AI by developing code-generating LLMs that balance innovation, security, and reliability. Our goal is to create a system that adapts to emerging challenges while maintaining strong functionality, demonstrating that safety and utility can work together to drive responsible technology development for the benefit of society.

By Virginia Tech
4 min read
Share

Yi Zeng - Team leader

Yi Zeng is a Ph.D. candidate in Computer Engineering at Virginia Tech under the supervision of Prof. Ruoxi Jia. His research focuses on AI safety and responsibility. Zeng has an extensive publication history in leading security and responsible AI venues, including USENIX Security, ACM CCS, NeurIPS, ICML, ICLR, ICCV, ACL, AsiaCCS, IJCAI, and TMLR. He obtained his Masters from UC San Diego and Bachelors from Xidian University. Zeng has industry experience interning at Meta and Sony AI, where he worked on techniques for responsible AI and security. His research has been featured in high-profile media outlets such as the New York Times, PCmag, the Register, and VentureBeat. Zeng's honors include the Best Social Impact Award from the ACL 2024, the Amazon Research Fellowship, and the Best Paper award at ICA3PP 2020.

Mahavir Dabas

Mahavir Dabas is a Masters student in Computer Engineering at Virginia Tech under Prof. Ruoxi Jia. He obtained his Bachelor's from the Indian Institute of Information Technology. Dabas has worked at ZS Associates as an NLP intern and at IIT Mandi as a Research Intern, focusing on combining reinforcement learning with cognitive science. He has also served as a Graduate Teaching Assistant in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. Currently, he works as a Graduate Research Assistant at the Responsible Data Science Laboratory at VT, focusing on the safety of large language models.

Adam Nguyen

Adam Nguyen is a third-year undergraduate student in Computer Science at Virginia Tech working under Prof. Ruoxi Jia's supervision. His research focuses on improving Large Language Model capabilities and reliability. He previously interned at Raytheon Technologies as a software engineer, developing enterprise software solutions. Currently, he is an Undergraduate Research Assistant in the Responsible Data Science Laboratory, contributing to research projects and building automated pipelines for experiments.

Tran Huynh

Tran Huynh is a first-year Ph.D. student in Computer Engineering at Virginia Tech, working under the supervision of Prof. Ruoxi Jia. She earned her Bachelor's degree in Computer Science from Vietnam National University. Huynh's research centers on AI safety, with her works published in venues including ECCV, AAAI, and EMNLP. She is currently a Research Assistant in the Responsible Data Science Laboratory at Virginia Tech, focusing on enhancing the safety alignment of large language models.

Sanchit Kabra

Sanchit is a first year Masters of Science in Computer Science student working under supervision of Prof. Rouxi Jia and Prof Chandan Reddy. He earned his Bachelors in CS from BITS Pilani, India. Kabra’s research centers around Responsible AI with a focus on evaluation and robustness. He has previously interned at Aalto University focusing on extreme classification. Currently, he is a Graduate Research Assistant at CS department working on concept alignment in multimodal models and code tasks on semi structured data.

Nikhil Reddy Billa

Nikhil is a first year Masters student in Computer Engineering at Virginia Tech working under Prof. Ruoxi Jia. He earned his Bachelors from National Institute of Technology Rourkela. Nikhil has worked as Software Engineer at NCR Corporation and ML Research Assistant at IIIT Hyderabad, focusing on Autonomous navigation in unstructured traffic and Adversarial Weather. Currently he is Graduate Research Assistant at Responsible Data Science Lab at VT, focusing on privacy in LLMs.

Bhuvishi Bansal

Bhuvishi Bansal is a Computer Science freshman at Virginia Tech, specializing in natural language processing (NLP) and the empirical evaluation of large language models. Her research explores bias detection, robustness analysis, and parameter-driven performance assessment, with a strong focus on enhancing the safety, fairness, and reliability of LLMs in real-world applications.

Rohan Praveen Chavan

Rohan Chavan is first year Masters of Science in Computer Engineering student. He has earned his Bachelors in IT from K.J. Somaiya College of Engineering, India. He has previously worked as a Intern at Colgate Palmolive Global Business Services, as an Robotic Process Automation developer where he helped the team to develop their inhouse LLM and also facilitated the integration of this LLM into their chatbot ecosystem. He is currently working for the Responsible Data Science Lab under guidance of Professor Ruxoi Jia on AI safety and safer, robust code generation by Large Language Models.

Ruoxi Jia - Faculty advisor

Ruoxi Jia is an assistant professor in the the Bradley Department of Electrical and Computer Engineering at Virginia Tech. She earned her PhD in the EECS Department from UC Berkeley and a B.S. from Peking University. Jia's recent work focuses on data-centric and trustworthy machine learning. Jia is the recipient of the NSF CAREER Award, the Dean's Award for Outstanding New Assistant Professor, the Chiang Fellowship for Graduate Scholars in Manufacturing and Engineering, the 8108 Alumni Fellowship, and the Okamatsu Fellowship, Cisco Research Awards, Amazon-VT Initiative Research Awards, and the Best Social Impact Paper Award at ACL 2024. She was selected for the Rising Stars in EECS in 2017. Jia’s work has been featured in multiple media outlets such as MIT Technology Review, New York Times, IEEE Spectrum, and Wired. Her work has been adopted in the financial sector and tech companies.

About the Author
Virginia Tech

Related content

Work with us

See more jobs See more jobs
Sr. Research Scientist III, WW Sustainability
US, WA, Seattle
Join the Worldwide Sustainability (WWS) organization where we capitalize on our size, scale, and inventive culture to build a more resilient and sustainable company. WWS manages our social and environmental impacts globally, driving solutions that enable our customers, businesses, and the world around us to become more sustainable. Sustainability Science and Innovation is a multi-disciplinary team within the WW Sustainability organization that combines science, analytics, economics, statistics, machine learning, product development, and engineering expertise to identify, evaluate and/or develop new science, technologies, and innovations that aim to address long-term sustainability challenges. We are looking for a Sr. Research Scientist to help us develop and drive innovative scientific solutions that will improve the sustainability of materials in our products, packaging, operations, and infrastructure. You will be at the forefront of exploring and resolving complex sustainability issues, bringing innovative ideas to the table, and making meaningful contributions to projects across SSI’s portfolio. This role not only demands technical expertise but also a strategic mindset and the agility to adapt to evolving sustainability challenges through self-driven learning and exploration. In this role, you will leverage your breadth of expertise in AI models and methodologies and industrial research experience to build scientific tools that inform sustainability strategies related to materials and energy. The successful applicant will lead by example, pioneering science-vetted data-driven approaches, and working collaboratively to implement strategies that align with Amazon’s long-term sustainability vision. Key job responsibilities - Develop scientific models that help solve complex and ambiguous sustainability problems, and extract strategic learnings from large datasets. - Work closely with applied scientists and software engineers to implement your scientific models. - Support early-stage strategic sustainability initiatives and effectively learn from, collaborate with, and influence stakeholders to scale-up high-value initiatives. - Support research and development of cross-cutting technologies for industrial decarbonization, including building the data foundation and analytics for new AI models. - Drive innovation in key focus areas including packaging materials, building materials, and alternative fuels. About the team Diverse Experiences: World Wide Sustainability (WWS) values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Inclusive Team Culture: 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. 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
Senior Research Scientist, Intelligent Talent Acquisition - Lead Generation & Detection Services
GB, MLN, Edinburgh
Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more, all with the shared goal of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments, and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems. A day in the life As a Research Scientist, you will partner on design and development of AI-powered systems to scale job analyses enterprise-wide, match potential candidates to the jobs they’ll be most successful in, and conduct validation research for top-of-funnel AI-based evaluation tools. You’ll have the opportunity to develop and implement novel research strategies using the latest technology and to build solutions while experiencing Amazon’s customer-focused culture. The ideal scientist must have the ability to work with diverse groups of people and inter-disciplinary cross-functional teams to solve complex business problems. About the team The Lead Generation & Detection Services (LEGENDS) organization is a specialized organization focused on developing AI-driven solutions to enable fair and efficient talent acquisition processes across Amazon. Our work encompasses capabilities across the entire talent acquisition lifecycle, including role creation, recruitment strategy, sourcing, candidate evaluation, and talent deployment. The focus is on utilizing state-of-the-art solutions using Deep Learning, Generative AI, and Large Language Models (LLMs) for recruitment at scale that can support immediate hiring needs as well as longer-term workforce planning for corporate roles. We maintain a portfolio of capabilities such as job-person matching, person screening, duplicate profile detection, and automated applicant evaluation, as well as a foundational competency capability used throughout Amazon to help standardize the assessment of talent interested in Amazon.
Applied Scientist II, Sponsored Products and Brands
US, NY, New York
About Sponsored Products and Brands The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. About our team The Search Ranking and Interleaving (R&I) team within Sponsored Products and Brands is responsible for determining which ads to show and the quality of ads shown on the search page (e.g., relevance, personalized and contextualized ranking to improve shopper experience, where to place them, and how many ads to show on the search page. This helps shoppers discover new products while helping advertisers put their products in front of the right customers, aligning shoppers’, advertisers’, and Amazon’s interests. To do this, we apply a broad range of GenAI and ML techniques to continuously explore, learn, and optimize the ranking and allocation of ads on the search page. We are an interdisciplinary team with a focus on improving the SP experience in search by gaining a deep understanding of shopper pain points and developing new innovative solutions to address them. A day in the life As an Applied Scientist on this team, you will identify big opportunities for the team to make a direct impact on customers and the search experience. You will work closely with with search and retail partner teams, software engineers and product managers to build scalable real-time GenAI and ML solutions. You will have the opportunity to design, run, and analyze A/B experiments that improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact while broadening your technical skillset. Key job responsibilities - Solve challenging science and business problems that balance the interests of advertisers, shoppers, and Amazon. - Drive end-to-end GenAI & Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Develop real-time machine learning algorithms to allocate billions of ads per day in advertising auctions. - Develop efficient algorithms for multi-objective optimization using deep learning methods to find operating points for the ad marketplace then evolve them - Research new and innovative machine learning approaches.
MTS-ML Infra, AGI
US, CA, San Francisco
Are you interested in a unique opportunity to advance the accuracy and efficiency of Artificial General Intelligence (AGI) systems? If so, you're at the right place! We are the AGI Autonomy organization, and we are looking for a driven and talented Member of Technical Staff to join us to build state-of-the art agents. AGI Autonomy is focused on developing new foundational capabilities for useful AI agents that can take actions in the digital and physical worlds. In other words, we’re enabling practical AI that can actually do things for us and make our customers more productive, empowered, and fulfilled. In this role, you will work closely with research teams to design, build, and maintain systems for training and evaluating state-of-the-art agent models. Our team works inside the Amazon AGI SF Lab, an environment designed to empower AI researchers and engineers to work with speed and focus. Our philosophy combines the agility of a startup with the resources of Amazon. Key job responsibilities * Evaluate performance of the training infrastructure, diagnose problems and address any gaps that exist. * Develop reliable infrastructure to schedule training and model evaluation jobs across clusters. * Work closely with researchers to create new techniques, infrastructure, and tooling around emerging research capabilities and evaluating models to meet customer needs. * Manage project prioritization, deliverables, timelines, and stakeholder communication. * Illuminate trade-offs, educate the team on best practices, and influence technical strategy. * Operate in a dynamic environment to deliver high quality software. About the team The Amazon AGI SF Lab is focused on developing new foundational capabilities for enabling useful AI agents that can take actions in the digital and physical worlds. In other words, we’re enabling practical AI that can actually do things for us and make our customers more productive, empowered, and fulfilled. The lab is designed to empower AI researchers and engineers to make major breakthroughs with speed and focus toward this goal. Our philosophy combines the agility of a startup with the resources of Amazon. By keeping the team lean, we’re able to maximize the amount of compute per person. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research.
Data Scientist, Data and Machine Learning, WWPS US Federal
US, MD, Jessup
Application deadline: Applications will be accepted on an ongoing basis Are you excited to help the US Intelligence Community design, build, and implement AI algorithms, including advanced Generative AI solutions, to augment decision making while meeting the highest standards for reliability, transparency, and scalability? The Amazon Web Services (AWS) US Federal Professional Services team works directly with US Intelligence Community agencies and other public sector entities to achieve their mission goals through the adoption of Machine Learning (ML) and Generative AI methods. We build models for text, image, video, audio, and multi-modal use cases, leveraging both traditional ML approaches and state-of-the-art generative models including Large Language Models (LLMs), text-to-image generation, and other advanced AI capabilities to fit the mission. Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based on customer needs. At AWS, we're hiring experienced data scientists with a background in both traditional and generative AI who can help our customers understand the opportunities their data presents, and build solutions that earn the customer trust needed for deployment to production systems. In this role, you will work closely with customers to deeply understand their data challenges and requirements, and design tailored solutions that best fit their use cases. You should have broad experience building models using all kinds of data sources, and building data-intensive applications at scale. You should possess excellent business acumen and communication skills to collaborate effectively with stakeholders, develop key business questions, and translate requirements into actionable solutions. You will provide guidance and support to other engineers, sharing industry best practices and driving innovation in the field of data science and AI. This position requires that the candidate selected must currently possess and maintain an active TS/SCI Security Clearance with Polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work. Key job responsibilities As a Data Scientist, you will: - Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate AI algorithms to address real-world challenges - Interact with customers directly to understand the business problem, help and aid them in implementation of AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production. - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder - Provide customer and market feedback to Product and Engineering teams to help define product direction - This position may require up to 25% local travel. About the team Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. 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 (diversity) conferences, inspire us to never stop embracing our uniqueness. 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. 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.
Senior Data Scientist, Data and Machine Learning, WWPS US Federal
US, MD, Jessup
Application deadline: Applications will be accepted on an ongoing basis Are you excited to help the US Intelligence Community design, build, and implement AI algorithms, including advanced Generative AI solutions, to augment decision making while meeting the highest standards for reliability, transparency, and scalability? The Amazon Web Services (AWS) US Federal Professional Services team works directly with US Intelligence Community agencies and other public sector entities to achieve their mission goals through the adoption of Machine Learning (ML) and Generative AI methods. We build models for text, image, video, audio, and multi-modal use cases, leveraging both traditional ML approaches and state-of-the-art generative models including Large Language Models (LLMs), text-to-image generation, and other advanced AI capabilities to fit the mission. Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based on customer needs. At AWS, we're hiring experienced data scientists with a background in both traditional and generative AI who can help our customers understand the opportunities their data presents, and build solutions that earn the customer trust needed for deployment to production systems. In this role, you will work closely with customers to deeply understand their data challenges and requirements, and design tailored solutions that best fit their use cases. You should have broad experience building models using all kinds of data sources, and building data-intensive applications at scale. You should possess excellent business acumen and communication skills to collaborate effectively with stakeholders, develop key business questions, and translate requirements into actionable solutions. You will provide guidance and support to other engineers, sharing industry best practices and driving innovation in the field of data science and AI. This position requires that the candidate selected must currently possess and maintain an active TS/SCI Security Clearance with Polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work. Key job responsibilities As a Data Scientist, you will: - Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate AI algorithms to address real-world challenges - Interact with customers directly to understand the business problem, help and aid them in implementation of AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production. - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder - Provide customer and market feedback to Product and Engineering teams to help define product direction - This position may require up to 25% local travel. About the team Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. 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 (diversity) conferences, inspire us to never stop embracing our uniqueness. 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. 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.
Senior Applied Scientist, Amazon
IN, KA, Bengaluru
Are you passionate about building data-driven applied science solutions to drive the profitability of the business? Are you excited about solving complex real world problems? Do you have proven analytical capabilities, exceptional communication, project management skills, and the ability to multi-task and thrive in a fast-paced environment? Join us a Senior Applied Scientist to deliver applied science solutions for Amazon Payment Products. Amazon Payment Products team creates and manages a global portfolio of payment products, including co-branded credit cards, instalment financing, etc. Within this team, we are looking for a Senior Applied Scientist who will be responsible for the following: Key job responsibilities As a Senior Applied Scientist, you will be responsible for designing and deploying scalable ML, GenAI, Agentic AI solutions that will impact the payments of millions of customers and solve key customer experience issues. You will develop novel deep learning, LLM for task automation, text 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 help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. As the Payment Products organization deals with problems that are directly related to payments of customers, the Senior Applied Scientist role will impact the large product strategy, identify new business opportunities and provides strategic direction, which will be very exciting.
MTS, Developer Experience
US, CA, San Francisco
Are you interested in a unique opportunity to advance the accuracy and efficiency of Artificial General Intelligence (AGI) systems? If so, you're at the right place! We are the AGI Autonomy organization, and we are looking for a driven and talented Member of Technical Staff to join us to build state-of-the art agents. Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where agents can redefine what AI makes possible. We’d love for you to join our lab and build it from the ground up! Key job responsibilities * Design and implement a modern, fast, and ergonomic development environment for AI researchers, eliminating current pain points in build times, testing workflows, and iteration speed * Build and manage CI/CD pipelines (CodePipeline, Jenkins, etc.) that support large-scale AI research workflows, including pipelines capable of orchestrating thousands of simultaneous agentic experiments * Develop tooling that bridges local development environments with remote supercomputing resources, enabling researchers to seamlessly leverage massive compute from their IDEs * Manage and optimize code repository infrastructure (GitLab, Phabricator, or similar) to support collaborative research at scale * Implement release management processes and automation to ensure reliable, repeatable deployments of research code and models * Optimize container build systems for GPU workloads, ensuring fast iteration cycles and efficient resource utilization * Work directly with researchers to understand workflow pain points and translate them into infrastructure improvements * Build monitoring and observability into development tooling to identify bottlenecks and continuously improve developer experience * Design and maintain build systems optimized for ML frameworks, CUDA code, and distributed training workloads About the team The team is shaping developer experience from the ground up. Building tools that enable researchers to move at the speed of thought: IDEs that seamlessly shell out to supercomputers, CI/CD pipelines that orchestrate thousands of agentic commands simultaneously, and build systems optimized for GPU-accelerated workflows. Your infrastructure will be the foundation that enables the next generation of AI research, directly contributing to our mission of building the most capable agents in the world.
Member of Technical Staff, ML Infra, AGI
US, CA, San Francisco
Are you interested in a unique opportunity to advance the accuracy and efficiency of Artificial General Intelligence (AGI) systems? If so, you're at the right place! We are the AGI Autonomy organization, and we are looking for a driven and talented Member of Technical Staff to join us to build state-of-the art agents. Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where agents can redefine what AI makes possible. We’d love for you to join our lab and build it from the ground up! Key job responsibilities * Design, build, and maintain the compute platform that powers all AI research at the SF AI Lab, managing large-scale GPU pools and ensuring optimal resource utilization * Partner directly with research scientists to understand experimental requirements and develop infrastructure solutions that accelerate research velocity * Implement and maintain robust security controls and hardening measures while enabling researcher productivity and flexibility * Modernize and scale existing infrastructure by converting manual deployments into reproducible Infrastructure as Code using AWS CDK * Optimize system performance across multiple GPU architectures, becoming an expert in extracting maximum computational efficiency * Design and implement monitoring, orchestration, and automation solutions for GPU workloads at scale * Ensure infrastructure is compliant with Amazon security standards while creatively solving for research-specific requirements * Collaborate with AWS teams to leverage and influence cloud services that support AI workloads * Build distributed systems infrastructure, including Kubernetes-based orchestration, to support multi-tenant research environments * Serve as the bridge between traditional systems engineering and ML infrastructure, bringing enterprise-grade reliability to research computing About the team This role is part of the foundational infrastructure team at the SF AI Lab, responsible for the platform that enables all research across the organization. Our team serves as the critical link between Amazon's enterprise infrastructure and the Lab's research needs. We are experts in performance optimization, systems architecture, and creative problem-solving—finding ways to push the boundaries of what's possible while maintaining security and reliability standards. We work closely with research scientists, understanding their experimental needs and translating them into robust, scalable infrastructure solutions. Our team has deep expertise in ML framework internals and GPU optimization, but we're also pragmatic systems engineers who build traditional infrastructure with enterprise-grade quality. We value engineers who can balance research velocity with operational excellence, who bring curiosity about ML while maintaining strong fundamentals in systems engineering. This is a small, high-impact team where your work directly enables breakthrough AI research. You'll have the opportunity to work with some of the most advanced AI infrastructure in the world while building the skills that define the future of ML systems engineering.
Senior Applied Scientist, Sponsored Products and Brands
US, NY, New York
About Sponsored Products and Brands The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. About our team The Search Ranking and Interleaving (R&I) team within Sponsored Products and Brands is responsible for determining which ads to show and the quality of ads shown on the search page (e.g., relevance, personalized and contextualized ranking to improve shopper experience, where to place them, and how many ads to show on the search page. This helps shoppers discover new products while helping advertisers put their products in front of the right customers, aligning shoppers’, advertisers’, and Amazon’s interests. To do this, we apply a broad range of GenAI and ML techniques to continuously explore, learn, and optimize the ranking and allocation of ads on the search page. We are an interdisciplinary team with a focus on improving the SP experience in search by gaining a deep understanding of shopper pain points and developing new innovative solutions to address them. A day in the life As an Applied Scientist on this team, you will identify big opportunities for the team to make a direct impact on customers and the search experience. You will work closely with with search and retail partner teams, software engineers and product managers to build scalable real-time GenAI and ML solutions. You will have the opportunity to design, run, and analyze A/B experiments that improve the experience of millions of Amazon shoppers while driving quantifiable revenue impact while broadening your technical skillset. Key job responsibilities - Solve challenging science and business problems that balance the interests of advertisers, shoppers, and Amazon. - Drive end-to-end GenAI & Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Develop real-time machine learning algorithms to allocate billions of ads per day in advertising auctions. - Develop efficient algorithms for multi-objective optimization using deep learning methods to find operating points for the ad marketplace then evolve them - Research new and innovative machine learning approaches. - Recruit Scientists to the team and provide mentorship.
See more jobs
View from space of a connected network around planet Earth representing the Internet of Things.
Get more from Amazon Science
Subscribe to our monthly newsletter

Amazon.com | Conditions of Use | Privacy | © 1996-2025 Amazon.com, Inc. or its affiliates

Social