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Lead Machine Learning Engineer- Data - job 19 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

$175000 / YEARLY (est.)
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max
$150000K
$200000K

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 looking for a passionate Lead Machine Learning Engineer- Data to join our Data and Artificial Intelligence Platform group based in Foster City, California. In this role, you’ll be a key player in shaping our data strategy, driving innovation with cutting-edge technologies that turn our vast data assets into powerful, purpose-fit solutions. You will lead the design and architecture of intricate, scalable data engineering platforms, dealing with everything from data pipelines to cloud-based data lakes. Exciting challenges await as you oversee the entire data lifecycle, from acquisition to analysis, while also developing a synthetic data engine for compliant privacy-enhanced data. You’ll have the chance to build and experiment with advanced modeling algorithms and become a champion for GenAI and Agentic AI, integrating them into both existing and new workflows. Guiding a talented team of engineers, you’ll foster a culture of innovation and learning, collaborating with business stakeholders to translate their needs into actionable insights. If you thrive in a dynamic environment where teamwork and fun combine, then Visa is the place for you! Join us and be part of a forward-thinking team dedicated to revolutionizing data and AI solutions.

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, you will lead the design and architecture of data engineering platforms, manage the entire data lifecycle, and implement a synthetic data engine. You’ll also build advanced modeling algorithms, champion GenAI technologies, and work closely with stakeholders to create actionable data solutions.

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What qualifications are required for the Lead Machine Learning Engineer- Data position at Visa?

Candidates for the Lead Machine Learning Engineer- Data role at Visa should possess strong expertise in Machine Learning and Data Engineering, along with a solid understanding of data platforms, security protocols, and compliance regulations. A proven track record mentoring junior engineers and a background in developing scalable data solutions are also essential.

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What opportunities for innovation exist in the Lead Machine Learning Engineer- Data role at Visa?

In the Lead Machine Learning Engineer- Data position at Visa, you will have the opportunity to drive innovation through unique data strategies, develop synthetic data solutions, and integrate cutting-edge GenAI technologies into workflows, thereby addressing complex challenges in the data and AI landscape.

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

Visa fosters a collaborative and fun team environment for the Lead Machine Learning Engineer- Data role. The team consists of diverse individuals who leverage their unique experiences and skills to create effective solutions, all while embracing a culture of continuous learning and innovation.

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

Visa is committed to the professional growth of its employees, including the Lead Machine Learning Engineer- Data. You will have access to mentorship, collaboration with talented peers, and opportunities to stay updated on emerging data trends, ensuring your skills and knowledge remain at the industry's forefront.

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Common Interview Questions for Lead Machine Learning Engineer- Data
Can you explain your experience with designing scalable data engineering platforms?

In your response, highlight specific projects where you designed data engineering platforms, focusing on the architecture, tools used, and the impact your solutions had on performance and scalability.

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How have you developed and implemented data governance policies?

Discuss instances where you created data governance policies. Include the challenges you faced and how you ensured compliance with regulations while keeping the data secure and accessible.

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What strategies do you use to lead and mentor a high-performing data team?

Share your leadership philosophy, detailing how you foster collaboration, encourage innovation, and support team members in professional development, illustrated with examples from your experience.

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

Explain your approach to professional development, whether through attending conferences, participating in online courses, networking with peers, or following industry publications.

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What methodologies have you used for building and testing machine learning models?

Discuss the specific methodologies you have employed in building and validating machine learning models, such as your approach to feature engineering, model selection, and testing, along with the results obtained.

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Describe an instance where you solved a complex data problem.

Provide a detailed account of a particularly challenging data problem you've faced, the steps you took to analyze and resolve it, and the positive outcome of your solution.

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What is your experience with GenAI technologies?

Discuss how you have previously integrated GenAI solutions into existing workflows and the impact this had on efficiency and output, citing specific projects or results.

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

Outline your practices for ensuring data security, including methods for securing sensitive data, implementing privacy-aware techniques, and ensuring compliance with relevant regulations and standards.

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Can you give an example of a successful collaboration with business stakeholders?

Detail a collaborative effort where you worked with business stakeholders to define their data needs and deliver actionable solutions. Include the processes you followed and the outcomes achieved.

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What tools and technologies are you most proficient in as a Machine Learning Engineer?

List the tools, programming languages, and technologies you are most comfortable with, and provide examples of how you've effectively utilized them in your work, emphasizing results and innovations derived from their use.

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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 2, 2025

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