Machine Learning Engineer- Sr. Consultant level- AI Governance - job 16 of 21

As a Machine Learning Engineer in the AI Governance team at Visa, your primary responsibilities include designing and building solutions with next-generation AI/ML and Generative AI technologies. You'll focus on creating a responsible AI platform, ensuring the accuracy and fairness of machine learning models, and implementing effective solutions using sound architectural principles. Additionally, you'll explore and evaluate new technologies to enhance AI governance strategies.

Candidates for the Machine Learning Engineer position at Visa should have a solid background in machine learning, data science, or a related field. Proficiency in utilizing tools for Generative AI, experience with agentic frameworks like LangGraph and LangChain, and a sound understanding of AI governance principles are essential. Strong programming skills and experience with APIs such as OpenAI are also critical for success in this role.

Visa leverages Generative AI by integrating innovative tools to expedite delivery and enhance the development of its AI Governance solutions. Specifically, the team utilizes frameworks that support retrieval-augmented generation and reinforcement learning to address the evolving challenges in ensuring responsible AI practices and robust governance.

In the hybrid work environment at Visa, you'll enjoy the flexibility of balancing in-office collaboration with remote work options. The expectation for in-office days will be confirmed with your Hiring Manager, helping you create a schedule that promotes productivity, teamwork, and innovation while aligning with the company's goals.

The AI Observatory product is crucial as it provides an organized inventory of machine learning models and AI systems, ensuring oversight throughout their entire lifecycle. This initiative fosters an environment of accuracy, transparency, and fairness in AI practices at Visa, thereby supporting the company's overall strategy for centralized AI excellence.

In responding to this question, detail a specific project that showcases your technical skills and problem-solving abilities. Highlight your contributions, emphasizing collaboration with others on the team and showcasing any innovative solutions you implemented.

Discuss your understanding of AI fairness and accountability metrics. Provide examples of how you have previously validated models for bias, conducted audits, or used particular algorithms designed to promote fairness in AI.

Engage in this conversation by outlining specific tools and frameworks you have experience with, such as LangGraph or LangChain. Explain why you prefer these tools, highlighting their benefits in terms of efficiency or specific project requirements.

Share your experience with Generative AI technologies, discussing any specific projects where you applied them. Your answer should include the benefits of using Generative AI in enhancing model efficiency and creativity in your solutions.

Identify potential challenges such as bias, lack of transparency, or evolving regulations. Offer your insights into strategies you would implement to mitigate these challenges, showcasing critical thinking and a proactive approach.

Demonstrate your ability to simplify complex ideas. Choose a concept like overfitting or model evaluation, and walk through it using relatable analogies or examples, which also showcases your communication skills.

Emphasize that data quality is foundational to any machine learning project. Discuss methods you've used to ensure high-quality data acquisition and preprocessing, and how these steps have directly influenced the outcomes of your projects.

Talk about your commitment to continuous learning, mentioning any online courses, webinars, or industry publications you follow. Demonstrate your enthusiasm for the field and how your knowledge translates into your work.

Provide a specific example of a model that underperformed. Describe how you performed diagnostics on the model, what adjustments were made, and the outcome, which shows your analytical and troubleshooting abilities.

Craft your response to reflect your research about Visa's commitment to responsible AI. Express your excitement about contributing to innovative projects like the AI Observatory, and how this aligns with your personal career goals.