Staff Machine Learning Scientist, Intern - PhD

3 Months ago • Upto 1 Years • Artificial Intelligence • Research & Development

Job Summary

Job Description

Job Details

Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

Visa Research is an organization that focuses exclusively on the scientific foundations of existing, emerging and future commerce-related technologies. With the establishment of a formal research organization and the associated long-term commitment to technology research, Visa joins the ranks of a small number of industry leaders with both the insight and ability to substantially influence and systemically impact the future.

The Research Intern will work with a team to conduct world-class research on data driven AI/ML initiatives and contribute to the long-term research agenda in large-scale data analytics and machine learning, as well as deliver innovative technologies and insights to Visa's strategic products and business.

This role represents an exciting opportunity to make key contributions to Visa's strategic vision as the world-leading digital payments company. The successful candidate must have an outstanding academic track record in fundamental and applied research with participation in developing innovations. The candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and excellent collaboration skills.

Job duties and projects could include:

  • Design and implement efficient and scalable machine learning algorithms.
  • 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:

  • Learning to super-learn: meta-learning for imbalanced task
  • Deep Reinforcement Learning: FX Trading and Confidence Modelling
  • GAI for transaction decisioning
  • Multi-task In-Context Learning with transaction data
  • Effective LLM fine-tuning: LLM pruning and combating catastrophic forgetting
  • High dimensional time series prediction

Qualifications

Basic Qualifications

  • Students pursuing a Ph.D. with a graduation date in December 2025 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

  • Machine Learning/AI: Previous research experience with Deep Learning, NLP, LLM, Graph Neural Networks, Reinforcement Learning
  • Proficiency with object-oriented programming languages, such as Python, Scala, Java or equivalent languages
  • Experience with large scale data processing using Hadoop and Spark is a plus
  • Strong verbal and written communication skills and an eagerness to collaborate with members of your team as well as other Visa teams.
  • Demonstrated ability to think outside the box and innovate.
  • The ability to learn new technologies fast
  • Good team player and excellent interpersonal skills
  • Good analytical and problem-solving skills
  • Demonstrated ability to lead and navigate through ambiguity

Additional Information

U.S. APPLICANTS ONLY: The estimated hourly range for a new hire into this position is $46/hr to $55/hr which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.

Work Hours: Varies upon the needs of the department.

This is a hybrid position: Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

Travel Requirements: This position requires travel 5-10% of the time.

Mental/Physical Requirements: This position will be performed in an office setting.  The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.

Visa is an EEO Employer.  Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.  Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.

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