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Lead Machine Learning Engineer- Data - job 15 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

$145000 / YEARLY (est.)
min
max
$130000K
$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

At Visa, we’re proud to announce an exciting opportunity for a Lead Machine Learning Engineer - Data based in Foster City, California! As a vital member of the Data and Artificial Intelligence Platform group, you’ll play an essential role in shaping the future of how we handle Visa’s data assets. You’ll be tasked with driving innovation by developing data solutions that not only harness cutting-edge technologies but also create real value for our customers. In this role, you’ll implement a comprehensive data strategy, focusing on leveraging our diverse data resources to fuel innovation through advanced data engineering and GenAI solutions, which includes creating a synthetic data engine. Your leadership and technical expertise will be invaluable as you guide and mentor junior engineers, ensuring that our data solutions are secure, scalable, and reliable. As part of a fast-growing team, you will work on complex AI and data challenges that seldom arise in the industry, while enjoying a collaborative environment filled with passionate professionals. We believe that teamwork and ongoing learning bring the best results, and here at Visa, you'll get to push the boundaries of what's possible in data and AI. If you are ready to take on these exciting challenges and make a meaningful impact in a dynamic field, we want to hear from you!

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

As the Lead Machine Learning Engineer - Data at Visa, you will oversee the design and architecture of scalable data engineering platforms, manage the entire data lifecycle, and develop innovative machine learning algorithms. Your role will involve creating a synthetic data engine for compliance and conducting experiments with various modeling techniques. You will also collaborate with business stakeholders to identify data-driven solutions that align with their needs.

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

To qualify for the Lead Machine Learning Engineer - Data role at Visa, candidates should have a strong background in Machine Learning and Data Engineering, with extensive experience in building robust data pipelines and architectures. Familiarity with GenAI and Agentic AI technologies, as well as a proven ability to lead teams and foster innovation, are also important qualifications for this position.

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What kind of projects can a Lead Machine Learning Engineer - Data expect to work on at Visa?

In the Lead Machine Learning Engineer - Data role at Visa, you can expect to work on a variety of innovative projects that involve developing purpose-fit data solutions using cutting-edge technologies. This includes designing cloud-based data lakes, implementing synthetic data engines, and integrating AI technologies into existing workflows to enhance Visa's data capabilities.

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How does Visa support the professional development of its Lead Machine Learning Engineers - Data?

Visa strongly emphasizes continuous learning and professional development for its Lead Machine Learning Engineers - Data. You will have opportunities to collaborate with some of the brightest minds in the industry, gain insights into emerging data and AI trends, and further your skills through hands-on experience in solving real-world, complex data challenges.

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Is the Lead Machine Learning Engineer - Data position at Visa a hybrid role?

Yes, the Lead Machine Learning Engineer - Data position at Visa is indeed a hybrid role. Your specific in-office expectations will be confirmed by your hiring manager, allowing for flexibility in your work environment while still fostering collaboration with your team.

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Common Interview Questions for Lead Machine Learning Engineer- Data
What experience do you have with developing machine learning algorithms?

When answering this question, highlight specific algorithms you've worked on, the challenges you faced, and how you overcame them. Make sure to mention any proprietary models you've developed or any use of widely adopted algorithms and frameworks in your previous roles.

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Can you describe your approach to managing data security and compliance in your projects?

In your response, focus on specific tools and methodologies you've implemented to ensure data security. Discuss your familiarity with regulations like GDPR or CCPA and how you've ensured compliance in your data handling practices.

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How do you prioritize projects when leading a data engineering team?

It's essential to outline your process for assessing project importance, including stakeholder feedback, business impact, and alignment with strategic goals. Discuss your experience with Agile or project management methodologies to illustrate your effectiveness.

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What strategies do you use to mentor junior engineers?

Discuss your mentoring philosophy and specific strategies you employ, such as regular one-on-one sessions, code reviews, and knowledge-sharing practices. Emphasize the importance of fostering a culture of learning and innovation in your team.

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Explain a complex data problem you solved and the outcome.

Share a specific example that highlights your analytical skills, the tools you used, and how your solution drove meaningful results for the organization. Specifying the impact on performance or efficiency will underscore your contributions.

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What is your experience with data pipeline and architecture design?

Provide details on projects where you've designed or improved data pipelines, the technologies used, and the key decisions made to enhance performance and scalability. This will demonstrate your technical proficiency.

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Which machine learning frameworks and tools are you most familiar with?

List the frameworks you have experience with, such as TensorFlow, PyTorch, or Scikit-Learn, and touch on projects where you've used them. This will validate your technical knowledge relevant to the Lead Machine Learning Engineer - Data role.

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How do you stay updated on emerging AI trends and technologies?

Discuss your engagement in professional communities, subscriptions to journals or blogs, participation in workshops, or any courses you've taken. This shows a commitment to your field and a proactive approach to learning.

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Can you describe your experience with synthetic data generation?

If applicable, provide insight into any synthetic data projects you've led or contributed to, explaining the objectives, methods employed, and the importance of privacy in your approach. This shows your niche expertise in a growing area of data engineering.

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How do you approach collaboration with business stakeholders?

Highlight your communication skills and methods you've used to build relationships with stakeholders. Describe how you translate technical insights into actionable solutions that align with business goals.

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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 3, 2025

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