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Lead Machine Learning Engineer- Data - job 4 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

Join Visa as a Lead Machine Learning Engineer - Data and become part of a forward-thinking team in Foster City, California, where data innovation meets cutting-edge technology! In this critical role within the Data and Artificial Intelligence Platform group, you’ll be tasked with developing robust data solutions that leverage our extensive data assets. Your main mission is to guide the creation of scalable data pipelines, robust data warehouses, and dynamic data lakes, both on-premises and in the cloud. You'll also have the chance to work on pioneering projects, such as creating a synthetic data engine that generates privacy-enhanced data. Collaboration is key here, as you will work closely with business stakeholders to translate their needs into actionable, data-driven solutions. Additionally, mentoring junior engineers is part of your responsibilities, ensuring that best practices around security and compliance are adhered to as you explore the endless possibilities of data and artificial intelligence. If you thrive on tackling complex challenges and enjoy working within a diverse team, this role at Visa presents an exciting opportunity to innovate and influence the future of data-driven solutions in the financial services industry. Ready to make an impact?

Frequently Asked Questions (FAQs) for Lead Machine Learning Engineer- Data Role at Visa
What responsibilities does a Lead Machine Learning Engineer - Data at Visa have?

As a Lead Machine Learning Engineer - Data at Visa, your responsibilities include overseeing the design and architecture of data engineering platforms, leading the development of a synthetic data engine, and managing the entire data lifecycle. You will also mentor junior engineers and collaborate with business stakeholders to ensure that our data solutions align with their needs. Ensuring compliance with data security and governance policies is also a significant part of your role.

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

Candidates applying for the Lead Machine Learning Engineer - Data position at Visa should have extensive experience in machine learning and data engineering. Proficiency in designing data pipelines, warehouses, and lakes is crucial, along with a strong understanding of compliance and security regulations. A background in developing synthetic data solutions and familiarity with GenAI technologies will definitely set you apart.

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How does the Lead Machine Learning Engineer - Data role at Visa foster innovation?

The Lead Machine Learning Engineer - Data at Visa drives innovation by developing advanced data solutions using cutting-edge technologies. You will champion new methodologies such as GenAI and Agentic AI, work on modeling algorithms, and automate data processes that enhance efficiency and data usability. Your leadership will help foster a culture that prioritizes continuous learning and creativity in tackling data challenges.

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What can one expect in terms of team dynamics in the Lead Machine Learning Engineer - Data role at Visa?

In the Lead Machine Learning Engineer - Data role at Visa, you can expect to collaborate with a diverse team of creative minds and industry experts. The environment promotes teamwork and fun while leveraging each member's unique experience to achieve collective goals. Together, you will tackle complex data challenges and explore innovative solutions, making work both fulfilling and enjoyable.

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What type of work environment can a Lead Machine Learning Engineer - Data expect at Visa?

At Visa, the work environment for a Lead Machine Learning Engineer - Data is hybrid, blending remote work flexibility with in-office collaboration. This setup allows for productive teamwork while accommodating personal preferences. You'll be part of a rapidly growing team that embraces innovation, ensuring that you stay engaged and connected with the latest trends in data and AI.

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Common Interview Questions for Lead Machine Learning Engineer- Data
Can you describe your experience with data pipelines as a Lead Machine Learning Engineer?

When answering this question, focus on specific projects where you designed or improved data pipelines. Mention the technologies you used, the challenges faced, and how your contributions resulted in better performance, scalability, or reliability. Highlight how these experiences align with the needs at Visa.

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What strategies do you employ to ensure data security and compliance in your projects?

Discuss your knowledge of industry standards and regulations regarding data security. Provide examples of policies you've implemented, how you assess risks, and the training you provide to your team to maintain compliance. Emphasize the importance of governance in your data strategy.

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

Explain the resources, communities, or publications you follow to keep abreast of trends. Mention any conferences you attend, online courses you take, or peer groups you engage with. This shows your commitment to continuous learning, an essential quality for a Lead Machine Learning Engineer at Visa.

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How do you approach mentoring junior engineers on your team?

Share your mentoring philosophy and provide examples of how you guide junior engineers. Discuss your strategies for fostering their growth, including setting goals, regular check-ins, and providing constructive feedback. Mention how this aligns with Visa's collaborative culture.

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What is your approach to integrating GenAI technologies into existing workflows?

Explain your process for introducing new technologies into established systems. Discuss assessing the value they bring, planning for implementation, and training team members. Provide insights on any existing frameworks you've used that would be beneficial in Visa's environment.

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Can you give an example of a challenging data problem you've solved?

Recall a specific instance where you faced a significant data challenge. Detail the problem, the steps you took to analyze the situation, the solution you implemented, and the impact it had on your project or organization. This demonstrates your critical thinking skills and practical experience.

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How do you prioritize tasks when managing multiple data projects?

Describe your time management strategies, including how you assess project importance, deadlines, and resource availability. Mention tools or frameworks you use to organize tasks and how you communicate priorities to your team, showcasing your leadership abilities.

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What machine learning frameworks are you proficient in, and how have you applied them in past projects?

Point out the specific machine learning frameworks you have experience with, such as TensorFlow, PyTorch, or Scikit-learn. Describe how you've applied these frameworks in practical applications, including details on the projects, results, and how you optimized model performance.

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How do you handle conflicts within your team?

Discuss your conflict resolution strategies, focusing on communication and collaboration. Provide an example of a past conflict and how you facilitated a resolution, emphasizing the importance of maintaining a healthy team dynamic, which is crucial for Visa's innovative environment.

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What do you think sets Visa apart in terms of data innovation and AI solutions?

Reflect on your understanding of Visa’s approach in the data and AI landscape. Highlight specific initiatives, technologies, or strategic partnerships that demonstrate Visa's commitment to innovation and its impact on the industry, linking your insights back to the role of a Lead Machine Learning Engineer.

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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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