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Lead Machine Learning Engineer- Data - job 18 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

$150000 / YEARLY (est.)
min
max
$120000K
$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

As a Lead Machine Learning Engineer- Data at Visa, you'll be stepping into a pivotal role within our Data and Artificial Intelligence Platform group, where we power the company's data assets to furnish valuable products and services to our global clientele. You'll be leading the charge in crafting innovative data solutions that utilize cutting-edge technologies. Your primary responsibility will be to execute a data strategy that amplifies our data capabilities through engineering and Generative AI solutions, including the groundbreaking development of a synthetic data engine. Additionally, you'll oversee the design and architecture of robust data platforms, ensuring security, scalability, and exceptional performance. Partnering closely with business stakeholders, you’ll translate their needs into actionable data-driven solutions while fostering a culture of continuous learning among junior engineers. With a blend of exciting challenges and a collaborative team environment, Visa is the place to hone your skills and contribute to pioneering advancements in Data and AI. If you’re looking to make a significant impact in a fast-growing team based in Foster City, California, join us in making a true difference.

Frequently Asked Questions (FAQs) for Lead Machine Learning Engineer- Data Role at Visa
What are the primary 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 ingestion to analysis, and developing advanced solutions such as a synthetic data engine. This role also involves leading a team of engineers, ensuring data security and governance, championing GenAI technologies, and partnering with business stakeholders to deliver 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 have a strong background in machine learning and data engineering, along with experience in developing and managing data platforms. A degree in computer science, engineering, or a related field is preferred along with familiarity with data modeling, data privacy regulations, and innovative AI technologies.

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How does the Lead Machine Learning Engineer- Data at Visa contribute to team culture?

At Visa, the Lead Machine Learning Engineer- Data plays a crucial role in fostering a collaborative and innovative team culture. This includes mentoring junior engineers, encouraging continuous learning, and promoting teamwork, which enriches the team environment and leads to greater collective success.

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What technologies are most important for a Lead Machine Learning Engineer- Data at Visa?

A Lead Machine Learning Engineer- Data at Visa should be well-versed in several technologies including data processing frameworks like Spark, data warehousing solutions, cloud platforms, and programming languages such as Python or R. Additionally, proficiency in machine learning frameworks and GenAI technologies will be integral to executing the role effectively.

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What is the work environment like for a Lead Machine Learning Engineer- Data at Visa?

The work environment for a Lead Machine Learning Engineer- Data at Visa is dynamic and collaborative, with a hybrid model that offers flexibility. You will be part of an innovative team that tackles large-scale data and AI challenges, all while contributing to exciting projects that shape the industry.

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

When responding, focus on specific projects where you implemented data solutions and machine learning models. Highlight the tools, technologies, and methodologies you used, such as Spark for data processing or TensorFlow for machine learning, showcasing your hands-on experience and impact in previous roles.

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How do you ensure data quality and integrity in your projects?

Discuss your approach to implementing quality checks and validation processes at various stages of the data lifecycle. Mention specific tools or practices you’ve used, like data profiling, testing, and establishing clear data governance policies to maintain high standards.

Join Rise to see the full answer
What strategies do you employ to keep up with emerging technologies in data and AI?

Share how you stay informed through continuous learning—mention attending industry conferences, joining online courses, or participating in communities. Highlight any recent technologies you've learned about and how they could apply to your role, demonstrating your proactive approach to innovation.

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Describe a challenge you faced in a previous data project and how you overcame it.

Provide a structured response that outlines the challenge, your thought process in addressing it, the actions you took, and the eventual outcome. This shows problem-solving skills and resilience, which are crucial for the role you're applying for.

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How do you prioritize tasks when managing multiple projects?

Explain your organizational methods, such as setting clear timelines, using project management tools, and maintaining open communication with stakeholders. Describe how you adapt to changes and manage stress while ensuring deadlines are met.

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What role does collaboration play in your work as a machine learning engineer?

Emphasize the importance of collaboration in fostering creativity and innovation. Provide examples of how you've worked with cross-functional teams, gathered requirements, and implemented feedback to enhance project outcomes.

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How do you approach mentorship and training for junior engineers on your team?

Describe your mentorship philosophy—how you support junior engineers' growth through shadowing, knowledge transfer sessions, or training resources. Highlight the importance of creating a supportive environment that encourages learning and skill development.

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Can you explain how you assess model performance and the criteria you use?

Discuss your approach to evaluating machine learning models—including metrics such as accuracy, precision, recall, and F1 score. Explain how you iteratively refine models based on performance feedback and employ techniques like cross-validation.

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What is your experience with cloud platforms and how have you used them in data projects?

Talk about the cloud platforms you’ve worked with, such as AWS, Azure, or Google Cloud, and describe specific instances where you leveraged cloud services for data storage, processing, or machine learning operations, showcasing your practical knowledge.

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How would you implement data governance and compliance in your role?

Share your understanding of data governance principles, compliance regulations, and how you would develop policies that ensure data privacy and security. Discuss collaboration with legal and compliance teams to maintain adherence to relevant laws and standards.

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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...

8880 jobs
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Full-time, hybrid
DATE POSTED
April 2, 2025

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