Principal Machine Learning Engineer- AI Platform - job 10 of 21

As a Principal Machine Learning Engineer at Visa, you will lead the technical roadmap of the AI Platform, collaborating with project, data science, and development teams to create data-driven business solutions. Your role will involve driving technical standards and best practices, designing architecture for AI services, and ensuring the scalability, security, and performance of systems. Additionally, you will mentor junior team members and help evolve talent within the organization.

To be a successful Principal Machine Learning Engineer at Visa, a strong background in machine learning system development is essential, ideally combined with experience in Agile methodologies. Proficiency in programming languages such as Golang, Java, and Python is crucial. A demonstrated ability in architectural design and implementation of complex systems, along with exceptional collaborative and coaching skills, is also important for this role.

Visa's AI Platform, specifically the Visa AI as a Service (VAIaS), enhances the payment industry by automating and optimizing processes through advanced AI and decision intelligence. By operationalizing AI capabilities, VAIaS ensures ongoing business value, improving the efficiency and reliability of transactions, which ultimately enhances the overall customer experience in payment services.

The work environment for a Principal Machine Learning Engineer at Visa is a hybrid model that encourages collaboration while also allowing for flexible remote work. Engineers are expected to work from the office 2-3 days a week, providing opportunities for in-person teamwork while still having the adaptability of remote work. This setup fosters a dynamic culture that balances innovation and productivity.

At Visa, a Principal Machine Learning Engineer will find ample opportunities for professional growth. You will be part of a leadership team where you can influence technical direction and standards. Additionally, mentoring junior team members allows for the development of leadership skills while working with cutting-edge technologies ensures you stay ahead in the industry.

In answering this question, focus on specific projects you have worked on, emphasizing your contributions and technologies used. Highlight any achievements, such as improved performance metrics, and explain how those experiences align with what Visa is doing with AI in payments.

Discuss various techniques such as cross-validation, ROC-AUC score, confusion matrix, and F1 score. Providing examples from your past work can illustrate your understanding and the relevance to Visa's AI Platform.

Explain your approach to scalability, including architectural choices and technologies you have used in past experiences. You might want to discuss distributed computing, load balancing, and optimizing performance, particularly in relation to Visa's AI services.

Share specific examples of best practices you've instituted in previous roles, such as coding standards, version control strategies, or documentation techniques. Make sure to connect these practices to the benefits for project success and team collaboration.

Discuss methods you use to stay current, such as attending conferences, following industry leaders on social media, participating in forums, or taking online courses. Mention any specific technologies or trends you are currently excited about and how they could relate to Visa's work.

Describe a systematic approach such as identifying data issues, checking model assumptions, or reviewing code. Providing an example can make your answer more impactful, showcasing your problem-solving skills.

Talk about experiences where you've had to balance different priorities, emphasizing your communication skills and your ability to work collaboratively to find solutions that align with the team's and stakeholders' needs.

Discuss how you've integrated Agile practices into your work, such as sprint planning, stand-ups, and retrospectives. Highlight how this experience can benefit the team dynamics and productivity at Visa.

Explain AI governance as crucial for ensuring compliance, ethics, and accountability in AI applications. Relate this to how Visa handles AI governance and the importance of maintaining public trust in AI technologies.

Discuss qualities such as effective communication, empathy, strategic thinking, and the ability to mentor others. Relate your answer to how these qualities play a role in fostering innovation and collaboration within the Visa team.