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Lead Machine Learning Engineer- Data - job 1 of 20

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.

What We Offer:

  • Exciting Challenges: We work at a scale rarely seen in the industry, solving complex data and AI problems across the entire stack, offering limitless opportunities to leverage and lead in this ever-growing field.

  • Teamwork and Fun: Each of us brings diverse and rich experiences to the team, enabling us to deliver much more than the sum of our parts and have fun at the same time.

  • Fantastic People: With strong leadership, you will have the opportunity to learn, collaborate, and deliver together with some of the best and most creative minds in the industry.

About the Role:

  • 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.

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 Lead Machine Learning Engineer- Data, Visa

As a Lead Machine Learning Engineer - Data at Visa in Foster City, you'll be stepping into a pivotal role within the Data and Artificial Intelligence Platform group. This dynamic team is dedicated to managing Visa's data assets and delivering invaluable insights and services to our customers. Your mission will be to innovate and design purpose-fit data solutions that harness the power of cutting-edge technologies, enhancing our data engineering and GenAI capabilities. You'll execute a data strategy that makes the most of our vast data resources, including the development of a synthetic data engine for creating privacy-enhanced synthetic data. As an expert in Machine Learning and Data Engineering, your responsibilities will include leading the architecture of robust data platforms, overseeing the entire data lifecycle, and mentoring junior engineers. You'll be at the heart of collaboration, ensuring that our platforms are secure, scalable, and reliable. With exciting challenges on the horizon and a strong team of creative minds, you'll have the chance to contribute to transformative AI projects while fostering a culture of continuous learning. Join us in this hybrid role, work alongside industry leaders, and become a vital part of a team that's shaping the future of data and AI at Visa.

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

The Lead Machine Learning Engineer - Data at Visa is responsible for designing and architecting scalable data engineering platforms, overseeing the entire data lifecycle from acquisition to analysis, and leading the development of a synthetic data engine. This role also involves experimenting with machine learning algorithms and integrating GenAI technologies into workflows, all while ensuring data security and compliance.

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What qualifications do I need to apply for the Lead Machine Learning Engineer - Data position at Visa?

To be a strong candidate for the Lead Machine Learning Engineer - Data position at Visa, you should have extensive experience in machine learning and data engineering, along with a solid understanding of data pipelines and data architecture. Familiarity with GenAI technologies and a commitment to mentoring junior team members is also essential. A proven track record of managing complex data projects will significantly enhance your application.

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How does the team culture at Visa for the Lead Machine Learning Engineer - Data role promote collaboration?

The team culture at Visa for the Lead Machine Learning Engineer - Data promotes collaboration through diverse experiences and strong leadership. Team members are encouraged to share ideas, foster innovation, and engage in fun, interactive problem-solving. This collaborative environment ensures that everyone contributes to delivering exceptional data solutions together.

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What types of projects will I work on as a Lead Machine Learning Engineer - Data at Visa?

As a Lead Machine Learning Engineer - Data at Visa, you will work on projects that involve creating scalable data platforms, developing transformative AI solutions, and implementing data-driven decision-making tools. You'll also be engaged in building synthetic data engines and enhancing organizational workflows through the application of GenAI and proactive AI methodologies.

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What opportunities for growth can I expect in the Lead Machine Learning Engineer - Data role at Visa?

In the Lead Machine Learning Engineer - Data role at Visa, there are significant opportunities for growth. You will collaborate with industry leaders, mentor a high-performing team, and engage with emerging technology trends. Visa's commitment to innovation means you'll constantly have access to new challenges and learning experiences that can enhance your professional development.

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Common Interview Questions for Lead Machine Learning Engineer- Data
Can you explain your experience with data engineering and machine learning?

When answering this question, provide specific examples of your previous work in data engineering and machine learning. Discuss projects where you designed architectures for data pipelines or developed machine learning models, emphasizing the tools and technologies you used.

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How do you approach developing a synthetic data engine?

Your answer should cover the key steps in developing a synthetic data engine, such as understanding data requirements, identifying privacy concerns, and using appropriate algorithms. Highlight your experience with ensuring compliance and scalability.

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What strategies do you use to lead a team in a fast-paced environment?

Discuss your management style, focusing on how you encourage innovation and collaboration within your team. Provide examples where you successfully led a team through tight deadlines while fostering a positive work culture.

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How do you keep up-to-date with emerging trends in data and AI?

Share your methods for staying informed about industry trends, such as attending conferences, participating in online courses, and following thought leaders. Highlight how you apply new knowledge to your work.

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Describe a challenging data project you've worked on and how you addressed it.

Be specific about the project details, the challenges faced, and the steps you took to overcome them. Emphasize your problem-solving skills and the impact of your solutions on the project's success.

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How do you ensure data security and compliance in your projects?

Describe the best practices you implement to ensure data security and safeguard against breaches. Discuss your familiarity with regulations and how you incorporate them into your workflows.

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What machine learning algorithms are you most comfortable working with?

List the algorithms you are familiar with, explaining when and why you would use each. Highlight any specific projects where you applied these algorithms successfully.

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How do you prioritize tasks in your role as a Lead Machine Learning Engineer?

Discuss the criteria you use for prioritizing tasks, such as stakeholder input, project deadlines, and the potential impact of projects. Share any tools or methodologies that assist you in task management.

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What is your process for mentoring junior data engineers?

Describe how you approach mentoring, including providing constructive feedback, facilitating skill development, and encouraging a growth mindset. Share a success story of a mentee's progress under your guidance.

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How would you collaborate with business stakeholders to gather requirements?

Talk about your approach to effective communication with stakeholders, ensuring that you ask the right questions and actively listen to their needs. Highlight how you translate these needs into actionable data solutions.

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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 4, 2025

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