Lead Machine Learning Engineer- Machine Learning Platform

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.

When you join Visa, you join a culture of purpose and belonging – where your growth is priority, your identity is embraced, and the work you do matters. We believe that economies that include everyone everywhere, uplift everyone everywhere. Your work will have a direct impact on billions of people around the world – helping unlock financial access to enable the future of money movement. 

This opportunity is in Visa's Machine Learning Platform.  The Machine Learning Platform provides soft infrastructure support to Visa's data scientists and researchers.  We enable the training of statistical and machine learning models via development and maintenance of a distributed computing stack.  Frameworks used in the stack are:  Kubernetes, Ray, Torch, Tensorflow, XGBoost, and Spark.  Development is primarily in Python and Go.   

We are a cross-functional team that interfaces both with internal data science and research clients as well as other hard and soft infrastructure teams.  

Responsibilities for this role include: 

--Monitoring of infrastructure health and problem solving to address persistent or urgent issues  

--Platform stabilization, including unit and integration testing  

--Interfacing with Kubernetes and data platform teams 

--Implementation of new infrastructure features  

--Mentorship of junior developers

--Pre-implementation architectural design

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

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.
• PhD in computer science, data science, statistics, or related field highly preferred.
• Proficiency in Python.
• Experience with Conda - must have skill.
• Experience with infrastructure components such as Kubernetes, Ray, Hadoop, Apache Spark.
• Experience training ML models.

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 175,100.00 to 253,950.00 USD 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.