Machine Learning Engineer- Sr. Consultant level- AI Governance - job 3 of 21

As a Senior Machine Learning Engineer at Visa, you’ll be on the front lines of AI Governance, responsible for designing and implementing robust AI solutions. Your primary duties will center around developing the AI Observatory product, ensuring a full lifecycle governance for machine learning models, and applying Generative AI technologies for expedited solution delivery. You will evaluate emerging technologies and prototype solutions, contributing to a transformative agenda in responsible AI.

To thrive as a Machine Learning Engineer at Visa, candidates typically need a strong background in machine learning algorithms, data structures, and AI technologies. Experience with Generative AI tools and programming languages such as Python or R is essential. A degree in Computer Science, Data Science, or a related field is often required, along with several years of industry experience focusing on AI governance and model management.

Visa’s commitment to Trustworthy AI in its AI Governance role involves a strict adherence to transparency, accuracy, and fairness in AI systems. As a Senior Machine Learning Engineer, you'll be responsible for developing solutions that uphold these principles while conducting thorough assessments and audits of AI models throughout their lifecycle. This guarantees that Visa’s AI solutions are deployed responsibly and in alignment with industry standards.

In the Machine Learning Engineer role at Visa, you'll have the opportunity to work with advanced tools and frameworks tailored for AI governance. You'll utilize various Generative AI technologies, including third-party solutions such as OpenAI and Llama, along with implementing Retrieval-Augmented Generation (RAG) techniques. Familiarity with frameworks like LangGraph and LangChain will be crucial as you innovate within this dynamic tech stack.

The work environment for a Machine Learning Engineer at Visa is collaborative and innovative, blending the flexibility of hybrid work. You’ll be interacting with experts in AI and Governance while contributing to strategic projects that have a significant impact on the business. The culture promotes continuous learning and adaptation, especially as AI technologies evolve, ensuring your skills are always at the cutting edge.

Responsible AI is crucial for ensuring that AI systems are ethical, fair, and transparent, which aligns closely with Visa's commitment to building trust with customers. In an interview, emphasize your understanding of these principles, and discuss how you would implement them in AI projects at Visa.

Highlight your strategies for staying informed, such as following leading AI research journals, attending relevant conferences, and participating in online courses. Demonstrating a passion for continuous learning shows you’re proactive and committed to integrating new knowledge into your work.

Discuss a specific project, outlining your methodology from conception through execution. Focus on the problem you were solving, the tools you utilized, and how you collaborated with others, underlining your role in delivering successful outcomes.

Explain your hands-on experience with Generative AI technologies and how you see them transforming business processes, enhancing model development, and delivering innovative solutions at Visa. Provide examples of how you've applied these technologies in past roles.

Illustrate your approach to model validation and testing. Discuss techniques like adjusting parameters, conducting bias assessments, and implementing fairness algorithms to ensure the model’s outcomes are equitable and reliable.

Discuss principles such as modularity, scalability, and maintainability. Provide examples of how adhering to these principles has led to successful AI implementations, and how it supports ongoing governance efforts.

Outline a systematic approach that includes assessing compatibility with existing systems, analyzing potential benefits and risks, and conducting a thorough cost-benefit analysis. Emphasize collaboration with stakeholders to evaluate the tool's impact on governance objectives.

Explain various strategies you employ, such as reviewing training datasets, implementing de-biasing techniques, and continuously monitoring model outputs. Stress the importance of diversity and inclusivity in data collection to mitigate bias.

Share your familiarity with managing the entire lifecycle of machine learning models, from development and testing through deployment and monitoring. Highlight your approach to maintaining model integrity and governance throughout this process.

Convey your admiration for Visa’s commitment to innovation and trustworthiness in AI. Discuss how the role aligns with your career aspirations, particularly your passion for responsible AI and your desire to contribute to groundbreaking initiatives within the company.