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Lead Machine Learning Engineer- Data - job 5 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

$165000 / YEARLY (est.)
min
max
$150000K
$180000K

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

At Visa, as a Lead Machine Learning Engineer- Data in our Foster City office, you'll be stepping into a vital role within the Data and Artificial Intelligence Platform group. This team is all about harnessing Visa's data assets to create innovative products and services that enhance customer experience. Imagine working with cutting-edge technologies and leading efforts to develop a synthetic data engine that enhances privacy while ensuring compliance! Your role will see you designing robust data platforms and overseeing the entire data lifecycle, from ingestion to analysis. Collaborating closely with junior engineers, you'll guide them in creating scalable and secure data solutions while maintaining high performance. We truly believe that teamwork can lead to great fun and outstanding results, and with the strong leadership at Visa, you’ll find yourself surrounded by fantastic people who are passionate about innovation. This is more than just a job; it’s an opportunity to be at the forefront of pioneering Data and AI within the industry. If you’re ready to take on exciting challenges and drive data strategies that define the future, we want to hear from you!

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?

As a Lead Machine Learning Engineer- Data at Visa, your key responsibilities include designing and architecting scalable data platforms, overseeing the entire data lifecycle from acquisition to analysis, and developing a synthetic data engine. You'll be leading a high-performing team, implementing data security and compliance protocols, and partnering with stakeholders to create actionable data-driven solutions.

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

To apply for the Lead Machine Learning Engineer- Data position at Visa, candidates typically need a strong background in machine learning and data engineering, often requiring advanced degrees in computer science, statistics, or related fields. Additionally, experience with data pipelines, cloud-based solutions, and proficiency in programming languages such as Python is highly valuable.

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How does Visa support the professional growth of a Lead Machine Learning Engineer- Data?

Visa is committed to fostering innovation and continuous learning among its teams. As a Lead Machine Learning Engineer- Data, you will have access to mentorship opportunities, collaborate with top industry professionals, and engage in projects that challenge your skills and encourage professional growth, making it an enriching work environment.

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What technologies will I work with as a Lead Machine Learning Engineer- Data at Visa?

In the role of Lead Machine Learning Engineer- Data at Visa, you will work with a variety of cutting-edge technologies. This includes cloud services for data storage, machine learning frameworks for developing models, and tools for data engineering and analytics. Your work may also involve GenAI technologies and more, depending on project requirements.

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What is the team culture like for the Lead Machine Learning Engineer- Data at Visa?

The team culture at Visa for the Lead Machine Learning Engineer- Data role is collaborative, innovative, and fun! Each member brings diverse experiences and skills, contributing to a culture where teamwork is valued and celebrated. You'll have the opportunity to learn from some of the best minds in the industry while helping shape the future of data and AI.

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Common Interview Questions for Lead Machine Learning Engineer- Data
Can you explain the importance of data pipelines in your past projects as a Lead Machine Learning Engineer?

When discussing data pipelines, it’s essential to highlight your experience in designing and maintaining scalable data ingestion processes. Focus on how these pipelines facilitate the efficient flow of data across various stages, enabling effective analysis and insights that drive decision-making.

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What methodologies do you use when developing a synthetic data engine?

While answering this question, explain the methodologies you employ, focusing on privacy-enhanced techniques, the generation of high-quality synthetic data, and how you ensure compliance with legal standards. Providing examples from past experiences can enhance your response.

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

To address data security and governance, discuss the frameworks you implement for compliance, how you manage data access, and outline procedures for maintaining data integrity. Emphasize your understanding of regulations and the importance of data privacy.

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Can you provide an example of a successful machine learning project you led?

When providing an example, detail the project's objectives, the technologies used, the challenges faced, and the solutions you implemented. Make sure to quantify results or improvements to showcase the project's impact effectively.

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What challenges do you foresee in the role of a Lead Machine Learning Engineer- Data and how would you tackle them?

In discussing challenges, mention topics like rapidly changing technologies or data compliance issues. Explain how your proactive approach to learning and collaborating with stakeholders prepares you to tackle these potential hurdles efficiently.

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How do you foster a culture of innovation within your team?

Articulate your strategies for encouraging creativity, which might include regular brainstorming sessions or collaborative projects. Discuss how mentorship and knowledge-sharing plays a role in maintaining a forward-thinking environment.

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What is your approach to translating business needs into technical data solutions?

In your response, emphasize communication skills and your ability to analyze business requirements. Discuss a systematic approach to gather input from stakeholders and how you ensure their needs are mapped effectively to technical solutions.

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How do you stay updated on emerging trends in data and AI?

Share your methods for professional development, including following industry news, attending conferences, and facilitating discussions with other professionals in the field. Highlight your eagerness to integrate the latest insights into your work.

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What tools would you recommend for effective data visualization?

Discuss your familiarity with various data visualization tools such as Tableau, Power BI, or open-source libraries like Matplotlib. Explain which tools are best suited for different purposes and provide rationale based on your experiences.

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What is your experience in mentoring junior engineers?

Illustrate your mentoring style, perhaps emphasizing hands-on guidance, regular check-ins, and providing opportunities for junior engineers to lead projects. Show how you value their growth and development as much as the project outcomes.

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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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