Staff Research Scientist Intern - Foundational AI

## About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. ## Job Description Visa’s Internship Program offers a 12-week immersive experience where you’ll work on impactful projects that advance Visa’s mission. As a Visa intern, you’ll build meaningful connections, strengthen your communication and business skills, and gain hands-on experience in a dynamic, global environment. ## Our Team Visa Research expands Visa’s technology research capabilities globally, conducting both applied and fundamental research. We partner closely with technology, product teams, academics, and governments to explore and develop technologies critical to the future of payments. ## Artificial Intelligence The GenAI Research team drives purpose-driven research to advance the next generation of AI for secure, intelligent, and scalable commerce. Our work spans: - Foundational AI: large language models, representation learning, embeddings, adaptive model training, and methods to advance fraud detection, risk modeling, personalization, and commerce intelligence. ## Job Duties - Conduct generative AI and LLM research focusing on scalable methods, model adaptation, evaluation, and applied use cases. - Design, implement, and evaluate AI algorithms for enterprise-scale systems. - Develop proof-of-concept prototypes to transition research into innovative products. - Optimize workflows for model training, inference, and data pipelines. - Prepare technical publications, reports, and intellectual property submissions. - Collaborate with engineering, product, and cross-functional partners to deliver impactful AI solutions. ## Qualifications ### Basic Qualifications - Students pursuing a Ph.D. with a graduation date in December 2027 or later ### Preferred Qualifications - Strong research record demonstrated by publications, patents, presentations, or technical contributions. - Experience in Generative AI, LLMs, deep learning, scalable ML, fine-tuning, model evaluation, or AI agents. - Knowledge of large-scale model training, efficient inference, or distributed systems. - Proficiency in Python, C++, Java, or similar languages. - Familiarity with big data frameworks (e.g., Hadoop, Spark) is a plus. - Ability to communicate complex concepts clearly and collaborate effectively. - Adaptability to evolving research priorities and problem-solving in an experimental setting.