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Senior Machine Learning Engineer- Machine Learning Platform - job 10 of 11

Visa is a world leader in digital payments, facilitating more than 215 billion payments transactions between consumers, merchants, financial institutions, and government entities across 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. 

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 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  

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

Average salary estimate

$140000 / YEARLY (est.)
min
max
$120000K
$160000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Machine Learning Engineer- Machine Learning Platform, Visa

At Visa, we are seeking a talented Senior Machine Learning Engineer for our Machine Learning Platform based in Foster City. If you're passionate about creating innovative solutions that drive financial inclusion, this role is perfect for you! As part of our dynamic team, you will provide essential soft infrastructure support to our data scientists and researchers, enabling them to develop and train machine learning and statistical models. You'll work with a diverse tech stack that includes Kubernetes, Ray, Torch, TensorFlow, XGBoost, and Spark, while primarily coding in Python and Go. Your role will involve monitoring infrastructure health and tackling any urgent issues that arise. You'll also play a key part in platform stabilization through unit and integration testing, and you'll interface regularly with our Kubernetes and data platform teams. This hybrid position allows for flexibility and collaboration, and you'll get to see firsthand how your work directly impacts billions of people worldwide. If you're looking to join a culture that values belonging, personal growth, and a strong sense of purpose, Visa is the place for you. Come help shape the future of money movement while being part of a team that’s as dedicated as you are!

Frequently Asked Questions (FAQs) for Senior Machine Learning Engineer- Machine Learning Platform Role at Visa
What are the responsibilities of a Senior Machine Learning Engineer at Visa?

As a Senior Machine Learning Engineer at Visa, responsibilities include monitoring the health of the infrastructure, addressing urgent issues, stabilizing the platform through thorough testing, and implementing new infrastructure features. Your technical prowess will enable visa’s data scientists to effectively train their machine learning models, contributing to the company's mission of enhancing financial access globally.

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What qualifications are needed for the Senior Machine Learning Engineer position at Visa?

To qualify for the Senior Machine Learning Engineer role at Visa, candidates should have a strong background in machine learning and distributed computing. Proficiency in programming languages such as Python and Go, alongside experience with frameworks like Kubernetes, TensorFlow, and Spark, is essential. A degree in computer science or a related field, coupled with proven experience in infrastructure support and machine learning model training, will set candidates apart.

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What technologies does the Machine Learning Platform at Visa use?

The Machine Learning Platform at Visa employs a diverse stack of technologies, including Kubernetes, Ray, Torch, TensorFlow, XGBoost, and Spark for distributed computing and model training. Proficiency in Python and Go is also crucial for developing robust infrastructure solutions that support our data science teams.

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Is the Senior Machine Learning Engineer position at Visa a remote or hybrid role?

The Senior Machine Learning Engineer position at Visa is a hybrid role, requiring some days in the office, which will be confirmed by the hiring manager. This arrangement fosters collaboration while also offering flexibility to work remotely.

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How does working at Visa impact the global community?

Working at Visa means directly impacting billions globally. The Senior Machine Learning Engineer will contribute to enhancing financial access through innovative payment technologies, empowering individuals, businesses, and entire economies to thrive in the digital payments space.

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Common Interview Questions for Senior Machine Learning Engineer- Machine Learning Platform
What experience do you have with distributed computing in machine learning?

To effectively answer this question, share specific examples of projects where you’ve utilized distributed computing frameworks like Kubernetes or Ray. Discuss your roles, the challenges faced, and how you overcame them, emphasizing the outcomes and your contributions to the team's success.

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Can you describe a challenging problem you solved in your previous machine learning projects?

When responding, highlight a specific challenge you encountered, delving into the context, your analytical approach, and the methods you employed to solve it. Discuss how your solution improved the project's results, showcasing your problem-solving skills and technical expertise.

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How do you ensure the infrastructure health for machine learning platforms?

Discuss your proactive monitoring strategies, such as implementing alerts for system failures, regular health checks, and performing root cause analysis on persistent issues. Emphasize your hands-on experience with tools and techniques used for maintaining infrastructure stability.

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What unit and integration testing strategies do you use while developing infrastructure features?

Detail your approach to unit and integration testing, specifying the types of tests you create and the frameworks or tools you use. Discuss how these strategies help catch bugs early, contribute to platform stability, and enhance collaboration in cross-functional teams.

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How would you collaborate with data scientists and researchers at Visa?

Share your approach to cross-functional collaboration, highlighting communication skills and tools you've used to facilitate teamwork. Discuss how you would gather requirements from data scientists and ensure they have the necessary infrastructure support for their machine learning tasks.

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What programming languages are you proficient in, and how do they apply to machine learning tasks?

Make sure to mention your proficiency in Python and Go, explaining how these languages are relevant for machine learning infrastructure development. Provide examples of tasks you've completed with these languages, such as building APIs, data processing, or developing algorithms.

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Describe your experience with specific machine learning frameworks like TensorFlow or PyTorch.

Discuss your hands-on experience with frameworks such as TensorFlow or PyTorch, detailing specific projects where you utilized them. Highlight the aspects of model training or experimentation you managed using these frameworks, emphasizing your technical depth and contributions.

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How do you stay updated with advancements in machine learning technologies?

Describe the resources you utilize to stay current, whether it's attending conferences, taking online courses, following industry leaders on social media, or engaging with professional communities. Emphasize your commitment to continuous learning in the fast-evolving field of machine learning.

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What is your approach to continuous integration and deployment (CI/CD) in machine learning projects?

Outline your strategies for implementing CI/CD pipelines for machine learning projects, discussing the tools you use (like Jenkins or GitLab CI) and how automation plays a role in testing, deploying, and monitoring machine learning models in production.

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What are the most critical qualities for a Senior Machine Learning Engineer at Visa?

Highlight the importance of technical expertise, problem-solving skills, and effective communication. Discuss how collaboration with diverse teams and the ability to translate complex technical concepts into actionable insights are crucial for success at Visa.

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Visa Inc. operates as a payments technology company worldwide. The company facilitates commerce through the transfer of value and information among consumers, merchants, financial institutions, businesses, strategic partners, and government entiti...

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Full-time, hybrid
DATE POSTED
April 9, 2025

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