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Machine Learning Engineer- Sr. Consultant level- AI Governance - job 17 of 21

AI Governance (AIG) Engineering team is part of the Data and AI Platform (DAP) technology organization in Visa. The team’s mission is to provide a Trustworthy AI – an engineering solution for Visa to achieve centralized AI excellence across Visa. We aim to develop, assess and deploy AI systems in a responsible and trustworthy way at Visa. This is a fantastic opportunity to join the effort undergoing in building the AI Observatory product for Visa. The AI Observatory product provides an inventory of ML models and AI systems, oversight for model’s full lifecycle, and governance of all model’s accuracy, transparency, fairness, and robustness. We are also uplifting domain-specific models to the unified AI Governance framework and streamline the modeling efforts to a centralized AI excellence across Visa.  

 As a Machine Learning Engineer in AI Governance engineering team, you will have the unique chance to make a direct and meaningful impact by delivering solutions that power AI Governance engineering solution. You will design, enhance, and build solutions dealing with the next generation AI/ML and Generative AI technology and be an agent of transformation. We deliver and support strategic goals and have a lasting impact on our enterprise. We aim to stay ahead of the curve adapting to the advancement of Generative AI and keep our business miles ahead of our competitors.    

 Essential Functions:

  • You will leverage sound architectural principles to implement effective and efficient solutions.  

  • You will use Generative AI tools to expedite your delivery. 

  • You will play a pivotal role in developing an advanced Responsible AI platform using the newest Generative AI technology. Your responsibility will include addressing evolving challenges in AI governance, and responsible and trustworthy AI. 

  • You will explore and evaluate emerging technologies, third-party solutions, and prototype and strategize their adaptation within Visa. Specifically, work with agentic frameworks such as LangGraph, LangChain, and APIs like OpenAI, Llama and implement Retrieval-Augmented Generation (RAG), Fine-Tuning, Reinforcement Learning techniques. 

This is a hybrid position. Expectation of days in office will be confirmed by your Hiring Manager. 

Average salary estimate

$140000 / YEARLY (est.)
min
max
$120000K
$160000K

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What You Should Know About Machine Learning Engineer- Sr. Consultant level- AI Governance, Visa

Are you ready to shape the future of AI governance with Visa's AI Governance Engineering team? As a Senior Consultant Machine Learning Engineer at Visa in Foster City, you'll be at the forefront of delivering a Trustworthy AI framework that ensures responsible and effective AI systems across the organization. Your mission will be pivotal in developing and enhancing the groundbreaking AI Observatory product, which focuses on the full lifecycle management of ML models and AI systems, emphasizing accuracy, fairness, and transparency. You’ll leverage cutting-edge Generative AI tools and architectural principles to build efficient and impactful solutions. By evaluating emerging technologies and agentic frameworks like LangGraph and LangChain, you’ll help Visa streamline its centralized AI excellence, paving the way for innovative transformation. In this hybrid role, you can expect collaboration with dynamic teams and a commitment to addressing the evolving challenges in AI governance. If you're passionate about developing responsible AI technologies and have the skills to drive strategic goals within Visa, we invite you to join us and make a real difference! Together, we will navigate the AI landscape and keep Visa ahead in this fast-evolving field.

Frequently Asked Questions (FAQs) for Machine Learning Engineer- Sr. Consultant level- AI Governance Role at Visa
What are the responsibilities of a Machine Learning Engineer at Visa?

As a Machine Learning Engineer at Visa, your responsibilities include designing and developing AI governance solutions, leveraging Generative AI tools for expedited delivery, and implementing effective frameworks and models. You'll work on the AI Observatory product, focusing on ML model management, transparency, and accuracy, while addressing evolving challenges in AI governance.

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

Candidates for the Machine Learning Engineer position at Visa should have a strong background in machine learning and AI technologies, proficiency in programming languages such as Python or Java, and experience with frameworks like LangGraph, LangChain, and various APIs. A passion for responsible AI development and prior experience in governance-focused AI systems will also be highly beneficial.

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What tools and technologies will a Machine Learning Engineer at Visa work with?

A Machine Learning Engineer at Visa will work with cutting-edge technologies and tools, including Generative AI platforms, APIs like OpenAI and Llama, as well as techniques such as Retrieval-Augmented Generation (RAG) and Reinforcement Learning. Familiarity with agentic frameworks and third-party solutions will enhance your strategic approach to AI governance at Visa.

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How does the AI Governance team at Visa ensure responsible AI implementation?

The AI Governance team at Visa ensures responsible AI implementation by developing an advanced Responsible AI platform that focuses on accuracy, fairness, and transparency. The team continuously evaluates emerging technologies and adapts strategic solutions to build trustworthy AI systems throughout the organization.

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What does the hybrid work model look like for the Machine Learning Engineer role at Visa?

The hybrid work model for the Machine Learning Engineer role at Visa involves a flexible arrangement of in-office and remote workdays. The specifics will be confirmed by your Hiring Manager, allowing you to balance collaboration with the convenience of working from home.

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Common Interview Questions for Machine Learning Engineer- Sr. Consultant level- AI Governance
Can you explain your experience with Generative AI technologies?

When answering this question, highlight specific projects where you used Generative AI tools. Discuss the challenges faced, the solutions implemented, and how these experiences align with the goals of Visa's AI Governance team.

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How do you ensure the accuracy and fairness of AI models?

To answer this effectively, explain your experience with testing and validation frameworks. Share specific methods you've used to measure accuracy and fairness, especially in the context of AI governance at previous roles.

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What architectural principles do you apply when building AI solutions?

Detail the architectural principles you consider, such as modularity, scalability, and maintainability. Discuss how these principles enhance the reliability of AI solutions, critical for the Machine Learning Engineer role at Visa.

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Describe a time you had to evaluate and implement a new technology.

Provide an example where you researched, prototyped, and integrated an emerging technology. Focus on the impact it had on your team's efficiency and how you can replicate this in the Machine Learning Engineer position at Visa.

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How would you approach building the AI Observatory product?

Discuss how you would leverage your technical skills to design the core functionalities of the AI Observatory. Mention your enthusiasm for collaborating with stakeholders to gather requirements and ensure that the product aligns with Visa's AI governance objectives.

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What experience do you have with model lifecycle management?

Share specific examples of how you manage models throughout their lifecycle, including deployment, surveillance, and retraining. Emphasize the importance of governance and accountability in this process, particularly for Visa.

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How do you keep yourself updated on emerging AI technologies?

Talk about your regular engagement with relevant literature, courses, online communities, and conferences. Highlight your willingness to learn and experiment with new tools—integral for the Machine Learning Engineer position at Visa.

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What role does ethical AI play in your work?

Discuss your understanding of ethical AI principles and how they guide your work in AI solutions. Provide examples of how you have implemented these principles in past projects, emphasizing their importance at Visa.

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Can you explain a technical challenge you've overcome in your prior work?

Choose a specific challenge related to AI or machine learning and explain how you approached it. Highlight your problem-solving skills and adaptability—key traits for a successful Machine Learning Engineer at Visa.

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Why do you want to work for Visa in the AI Governance space?

Express your passion for AI governance and the mission of Visa. Discuss how your values align with Visa's commitment to delivering trustworthy AI, and how your skills can contribute to the ongoing initiatives in this field.

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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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