Senior Machine Learning Engineer- Data Science Platform

Posted 4 Days Ago
Foster City, CA
Junior
Fintech • Information Technology • Payments
Join a world leader in payments and technology!
The Role
The Senior Machine Learning Engineer will design and implement machine learning solutions to enhance merchant data, ensuring data quality and discovering insights. The role requires expertise in machine learning, big data ecosystems, MLOps, and automation frameworks.
Summary Generated by Built In

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

About the Role:

We are looking for a senior machine learning engineer to join our merchant data platform data science and modeling team to help build next generation AI powered merchant ecosystem.

Essential Functions:

In this role, you will help build machine learning solutions to enhance merchant data, discover insights, ensure data quality and power cross functional peers to unleash merchant data potential.

  • MLE who has a good combination of science and engineering experiences (but machine learning / science experiences is more important than engineering experience)
  • For science perspective, we would like this role to have hands on experience designing production level solutions (ideally with NLP / deep learning)
  • For engineering experience, we look for someone who understands big data ecosystem and MLOps (production ML engineering).

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.

Qualifications

Basic Qualifications:

  • 2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)

Preferred Qualifications:

  • 3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)
  • Bachelor's degree with 2+ years experience or master degree in computer science, Machine Learning, Data Science or related fields
  • Skilled in SQL, Python and basic libraries for machine learning such as scikit-learn and Pandas, as well as Jupyter Notebook
  • Experience with Big Data and analytics in general leveraging technologies like
  • Hadoop, Spark, and Query Engines
  • Relevant experiences in modeling techniques such as logistic regression, Naive Bayes, SVM, decision trees, natural language processing or neural networks
  • Experience in DevOps and CI/CD tooling and concepts such as docker and
  • Jenkins
  • Experience in Automation framework such as Airflow or Metaflow
  • Understand ML infrastructure concepts such as feature store, batch inference
  • and model pipeline orchestration

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 129,400.00 to 182,750.00 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.

Top Skills

Python
The Company
HQ: San Francisco, CA
26,500 Employees
On-site Workplace
Year Founded: 1958

What We Do

At Visa, we are driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid. As our products and technology have evolved with the world, Visa remains ubiquitous, reaching new customers in new and often invisible ways. We are at the center of this digital revolution with a network that connects people with over 80 million businesses all over the world. And Visa’s network is expanding, accelerating our growth. Our resilient business model, with its strong track record of success, will provide you with amazing opportunities to grow in your career, as well.

We are looking for people like YOU. Come join a people-centric company where you can invest in your career.

For more information, visit visa.com/about, visacorporate.tumblr.com and @VisaNews on Twitter.

Why Work With Us

Our employees are our company. Creating an inclusive and diverse workplace has been our key priority. With our purpose to “uplift everyone, everywhere” as our guide, we’re building an environment where diverse backgrounds and perspectives are celebrated and drive success inside our company and out in our communities.

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