Staff Research Scientist – Intern

Job Description

Our Team

Visa Research is a research organization part of the company's effort on expanding its technology research capabilities globally. We conduct both applied and fundamental research while engaging with the company's technology and product teams, business partners, academics, and governments, to explore and develop technologies that are critical to the payments industry in the future.

Artificial Intelligence

Our mission at the Artificial Intelligence team is to unlock the hidden value in these massive high-quality financial data and decode the language of transactions to drive innovation in the payment industry and beyond. We conduct applied research in machine learning and related fields to deliver unique insights and capabilities to our partners and clients to help them grow their businesses. Our research areas include deep learning applications in financial data, supervised and unsupervised representation learning, predictive modeling for fraud and risk management, consumer behavior modeling, recommendation systems, payment foundational models, scalable machine learning systems, privacy preserving data analytics, and related fields.

Job duties and projects could include:

• Design and implement efficient and scalable machine learning/Artificial Intelligence algorithms
• Leveraging large language models in applications, improving them via techniques and find ways to integrate to Visa data
• Improving the workflow of model training and serving, data pipelines and resource management
• Connecting cutting edge academic research with user-facing next generation products
• Integrate data processing and training pipelines with big data infrastructure.
• Develop proof-of-concept prototypes with fast iteration and experimentation.
• Develop and maintain software design documentation, test cases, and performance evaluation.
• Works within an agile software engineering methodology and collaborative team development architecture.
• Deliver high-impact intellectual property values through research publications and patents • Collaborate with team members to deliver innovative technologies, insights and products to Visa business units to resolve their significant product pain-points and create new growth opportunities
• Work with team members and cross-functional teams (internal/external) that include representation from Technology, Product, Operations, Market Research, etc.

Past intern projects have included:

• Transaction Generation for Merchant Category
• Truthful LLMs via RAG
• Efficient Transformer
• Distributed training architecture for large models

Qualifications

Basic Qualifications

• Students pursuing a Ph.D. with a graduation date in December 2026 or later
• Strong communications skills, specifically, the absence of repeated grammatical or typographical errors, clear and concise written and spoken communications that demonstrate professional judgment.

Preferred Qualifications

• A track record of strong research results as demonstrated by papers in reputed journals and conference proceedings, patents, and presentations at conferences
• AI/Data Analytics: research experience with Deep Learning, Machine Learning, Scalable GenAI, Large Language Model, Advance AI research, and Fine Tuning LLM
• Strong verbal and written communication skills and an eagerness to collaborate with members of your team as well as other Visa teams.
• Hands-on experience with large scale model training including data preparation and model parallelization.
• Proficiency with object-oriented programming languages, such as Python, C++, Java or equivalent languages
• Experience with large scale data processing using Hadoop and MapReduce is a plus
• Demonstrated ability to think outside the box and innovate.
• The ability to take on challenges and address problems head-on
• Strong ability to collaborate
• Highly driven, resourceful and results oriented
• Good team player and excellent interpersonal skills
• Good analytical and problem-solving skills
• Demonstrated ability to lead and navigate through ambiguity