Machine Learning Engineer- Sr. Consultant level- AI Governance - job 8 of 21

As a Machine Learning Engineer - Sr. Consultant at Visa, you will be primarily responsible for designing, enhancing, and building solutions that leverage cutting-edge Generative AI technology. You will play a pivotal role in the development of the Responsible AI platform, tackle challenges related to AI governance, and contribute to the AI Observatory product that oversees the full lifecycle of models and AI systems, ensuring their accuracy, fairness, and transparency.

To succeed as a Machine Learning Engineer - Sr. Consultant at Visa, candidates should possess a strong background in machine learning, software development, and AI governance. Typically, a degree in Computer Science or a related field is preferred, alongside experience in AI/ML technologies, Generative AI tools, and familiarity with APIs like OpenAI and Llama. Being comfortable with architectural principles for developing effective solutions is also essential.

Visa's AI Governance Engineering team is committed to ensuring Trustworthy AI by implementing stringent oversight and governance protocols throughout the development and deployment of AI systems. This includes monitoring model accuracy, transparency, fairness, and robustness as part of the AI Observatory initiative, which acts as a centralized resource for managing AI systems responsibly.

In the role of Machine Learning Engineer - Sr. Consultant at Visa, you will engage with a variety of innovative technologies and frameworks such as LangGraph, LangChain, and APIs like OpenAI. Additionally, you will implement techniques like Retrieval-Augmented Generation (RAG) and Fine-Tuning as part of your responsibilities to enhance AI governance solutions.

The Machine Learning Engineer - Sr. Consultant position at Visa offers a hybrid work model, blending remote work flexibility with in-office collaboration. The specific number of in-office days will be confirmed by your Hiring Manager, ensuring a balance that promotes both productivity and team interaction.

In answering this question, be sure to highlight specific projects where you've implemented Generative AI tools. Talk about your role in developing solutions and any measurable outcomes that resulted from your work. This demonstrates not only your experience but also your impact.

Discuss techniques you've employed to validate models, such as cross-validation and fairness testing. Mention how you incorporate continuous monitoring and adjustments to uphold accuracy and fairness in line with governance best practices, showcasing a proactive approach.

Focus on core principles such as accountability, transparency, and ethical considerations in AI development. Relate these principles to previous experiences where you've implemented governance strategies, reinforcing your commitment to Trustworthy AI.

If you have experience with these frameworks, outline a project where you utilized them. Explain the challenges faced, solutions developed, and how these frameworks facilitated your efforts in AI governance and model management.

Mention activities like attending conferences, participating in workshops, or engaging with online communities. Highlight any relevant courses or certifications that demonstrate your ongoing commitment to learning in the fast-evolving AI landscape.

Provide a brief overview of the project, the specific challenges encountered, and how you handled them. Emphasize problem-solving skills and your ability to adapt to changing requirements, which are vital in the field of AI.

Discuss approaches like implementing transparent decision-making processes and continuously assessing model impacts on different demographics. This demonstrates an understanding of ethical implications while working towards AI solutions.

Emphasize collaboration, communication, and the value you place on diverse inputs. Give examples of how you've effectively worked within a team, showcasing your ability to unite different viewpoints to achieve common goals.

Identify key metrics such as accuracy, precision, recall, F1 score, and AUC-ROC. Explain how these metrics help inform the effectiveness of a model and how you adjust models based on their performance.

Tailor your response to reflect your interest in Visa's commitment to Trustworthy AI and technological innovation. Express your enthusiasm for contributing to meaningful projects that align with your values in the AI governance field.