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
The Data and Artificial Intelligence Platform group is a key component of Visa’s Technology organization, providing the enabling technology and processes to handle Visa’s data assets and deliver valuable information, products, and services to customers. Our team delivers secure, high-quality, and easy-to-use Visa core data assets, along with reliable and scalable data platforms. Our platform operationalizes the delivery of AI and decision intelligence to ensure ongoing business value to Visa and our clients.
As a Lead Machine Learning Engineer- Data with expertise in Machine Learning and Data Engineering, you will drive innovation in developing purpose-fit data solutions using cutting-edge technologies. You will be responsible for executing a data strategy that leverages our data assets to drive innovation through data engineering and GenAI solutions, including developing a synthetic data engine. You will also guide and mentor junior engineers, ensuring security, scalability, performance, and reliability in all data solutions. As an individual contributor based in Foster City, California, USA you will be reporting to Sr. Director of Data as a Service (DaaS) team. This team is growing fast! Join us and be an integral part of the group that is at the leading edge of pioneering Data and AI.

BASIC QUALIFICATIONS:

• 10 or more years of work experience with a Bachelor’s Degree or at least 8 years of work experience with an Advanced Degree (e.g. Masters/ MBA/JD/MD) or at least 3 years of work experience with a PhD.

PREFERRED QUALIFICATIONS:

• 12 or more years of work experience with a Bachelor’s Degree or 8-10 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 6+ years of work experience with a PhD.
• Expertise in leading-edge areas such as Machine Learning, Deep Learning, Stream Computing, and MLOps.
• Expertise with GenAI technologies (e.g., Large Language Models, NLP) and RAG-based architecture and vector databases.
• Strong proficiency in programming languages like Java, Scala, SQL, and REST.
• Any experience with Machine Learning Model Deployment/Development and/or Predictive Modeling is highly preferred.
• Experience with Prometheus, Grafana, Docker or Kubernetes is highly preferred.
• 12+ years of hands-on experience and a proven track record of building and deploying complex data pipelines and architectures using the latest technologies.
• Expertise in on-prem and cloud-based data platforms (AWS, Azure) and related data storage and processing tools (e.g., Databricks, S3).
• Relevant exposure to modeling techniques such as logistic regression, SVM, decision trees, or neural networks.
  Additional Information
  Work Hours: Varies upon the needs of the department.
  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.
  U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is $194,600 to $282,150 per year, 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

• Lead the design and architecture of robust, scalable data engineering platforms and infrastructure, including data pipelines, data warehouses, and data lakes (on-prem and cloud-based).
• Oversee the entire data lifecycle, from data acquisition and ingestion to transformation, storage, and analysis.
• Develop a synthetic data engine to generate on-demand privacy enhanced synthetic data where actual production data cannot be used, ensuring scalability and compliance.
• Build and experiment with modeling and scoring algorithms, including custom algorithms and packaged tools based on machine learning, analytics, and statistical techniques.
• Champion the adoption of GenAI and Agentic AI technologies and develop strategies to integrate them into existing workflows or build new ones.
• Ensure data security, privacy, governance, and compliance with all relevant regulations, and develop and implement auditable policies and procedures.
• Lead and guide a high-performing data engineering and ML team, fostering a culture of innovation and continuous learning.
• Partner with business stakeholders to understand their needs and translate them into actionable data-driven solutions.
• Stay up-to-date on emerging data and AI trends and technologies.
  This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.
  Qualifications