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Senior Machine Learning Engineer - job 22 of 25

About the Role:

Visa AI as a Service (VAIaS) operationalizes the delivery of AI and decision intelligence to ensure their ongoing business values. Built with composable AI capabilities, privacy-enhancing computation, and cloud-native platforms, VAIaS automates the updates to data, models, and applications. Combined with strong AI governance, VAIaS optimizes the performance, scalability, interpretability and reliability of AI models and services. If you want to be in the exciting payment and AI space, learn fast, and make big impacts, Visa AI as a Service is an ideal place for you!

This position is for a Senior Engineer with solid development experience who will focus on creating new capabilities for Visa AI as a Service while maturing our code base and development processes. In this position, you are first a passionate and talented developer that can work in a dynamic environment as a member of Agile Scrum teams.  Your strong technical leadership, problem-solving abilities, coding, testing and debugging skills is just a start.  You must be dedicated to filling product backlog and delivering production-ready code.  You must be willing to go beyond the routine and prepared to do a little bit of everything.

You will be an integral part of the development team, sometimes investigating new requirements and design and at times refactoring existing functionality for performance and maintainability, but always working on ways to make us more efficient and provide better solutions to our end customers. The role is for a self-organized individual with knowledge of web application and web service development. The candidate will perform hands-on activities including design, documentation, development and test of new functionality. Candidate must be flexible and willing to switch tasks based on team’s needs.

Essential Functions

  • Collaborate with project team members (Product Managers, Architects, Analysts, Software Engineers, Project Managers, etc.) to ensure development and implementation of new data-driven business solutions

  • Drive development effort End-to-End for on-time delivery of high-quality solutions that conform to requirements, conform to the architectural vision and comply with all applicable standards

  • Responsibilities span all phases of solution development including:

  • Collaborate with senior technical staff and PM to identify, document, plan contingency, track and manage risks and issues until all are resolved

  • Present technical solutions, capabilities, considerations, and features in business terms. Effectively communicate status, issues, and risks in a precise and timely manner

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

Average salary estimate

$135000 / YEARLY (est.)
min
max
$120000K
$150000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Machine Learning Engineer, Visa

Join Visa AI as a Service in Austin as a Senior Machine Learning Engineer and dive into the exciting world of AI and payment solutions! Here, we operationalize the delivery of AI and decision intelligence, ensuring we maximize business value at every step. Your primary focus will be developing new capabilities that enhance our AI systems while also refining our codebase and development processes. This role is perfect for those who thrive in a dynamic Agile environment and are passionate about coding and problem-solving. As a key player in our Scrum teams, you’ll contribute hands-on to design, documentation, and development, constantly collaborating with Product Managers, Software Engineers, and Analysts. You'll enjoy a mix of responsibilities that include investigating new requirements, refactoring existing functionality to improve performance, and creating data-driven solutions that really make an impact. We believe in strong AI governance, and you'll help drive projects from inception to on-time delivery, ensuring all solutions meet architectural standards. Plus, you can look forward to a hybrid working environment where you alternate between remote work and being in the office 2-3 days a week. If you’re ready to take your career to the next level and make significant contributions to AI in the payment space, we want to hear from you!

Frequently Asked Questions (FAQs) for Senior Machine Learning Engineer Role at Visa
What are the responsibilities of a Senior Machine Learning Engineer at Visa AI as a Service?

As a Senior Machine Learning Engineer at Visa AI as a Service, your responsibilities include collaborating with cross-functional teams to develop data-driven business solutions, driving end-to-end development efforts, managing risks and issues, and presenting technical solutions in a business-friendly manner. You'll work on both new feature development and improving existing functionality to enhance system performance.

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What qualifications are necessary for a Senior Machine Learning Engineer at Visa AI?

To qualify for the Senior Machine Learning Engineer position at Visa AI, candidates should have solid development experience in machine learning, strong technical leadership skills, and a background in web application and service development. Familiarity with Agile methodologies and a problem-solving mindset are also essential.

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What does a day look like for a Senior Machine Learning Engineer at Visa AI in Austin?

A typical day for a Senior Machine Learning Engineer at Visa AI involves collaborating with team members, identifying new requirements, developing and testing features, and continuously improving the codebase. Your day will also include joining Agile meetings, where you discuss progress and challenges with your team, ensuring everyone is aligned.

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Is remote work available for the Senior Machine Learning Engineer role at Visa AI?

Yes, the Senior Machine Learning Engineer role at Visa AI is a hybrid position. You can work remotely while also being expected to be in the office 2-3 days a week, based on business needs. This flexibility allows you to balance collaboration with your team and focused work at home.

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What makes Visa AI as a Service an exciting place for a Senior Machine Learning Engineer?

Visa AI as a Service is an exciting place for a Senior Machine Learning Engineer because it operates at the cutting edge of AI and payment technology. You'll have the opportunity to work on innovative projects that directly impact the way businesses leverage AI, all while developing your career in a nurturing environment.

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Common Interview Questions for Senior Machine Learning Engineer
Can you explain a challenging machine learning project you've worked on?

When answering this question, provide a specific example that outlines the project's objective, the challenges faced, and the ultimate outcome. Highlight your problem-solving skills and how you collaborated with your team to overcome difficulties.

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How do you ensure the integrity and quality of your machine learning models?

Discuss your experience with model validation techniques, such as cross-validation and performance metric analysis. Emphasize the importance of continuous monitoring and improvement of models post-deployment.

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What programming languages are you most comfortable with for machine learning?

Mention specific languages, ideally Python or R, and explain your experience with libraries such as TensorFlow or scikit-learn. If applicable, provide examples of projects where you've utilized these languages effectively.

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Describe your experience with Agile methodologies in machine learning projects.

Discuss how you have applied Agile practices in your previous roles, focusing on your ability to adapt to changing requirements, collaborate within cross-functional teams, and deliver high-quality results in iterative cycles.

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How do you stay current with advancements in the machine learning field?

Share your methods for keeping up with the latest trends, such as attending industry conferences, participating in online courses, or following relevant publications. This shows your commitment to lifelong learning.

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Can you explain a situation where you had to refactor existing code?

Provide a detailed account of a specific instance where you refactored code, explaining the reasons behind your decision and how the changes improved performance, readability, or maintainability of the software.

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How do you approach collaboration with non-technical stakeholders?

Discuss your experience with translating technical concepts into business terms, how you actively listen to stakeholders' needs, and your strategies for ensuring clear communication to avoid misunderstandings.

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What strategies do you use to manage risks in machine learning projects?

Outline the steps you take to identify potential risks upfront, such as thorough project planning and leveraging feedback loops, as well as how you communicate and manage these risks with your team.

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Describe a time when your machine learning model did not perform as expected.

Talk about a specific case when this happened, the steps you took to investigate the issue, how you implemented changes to address the problem, and what you learned from the experience to prevent future occurrences.

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What role does data preprocessing play in your machine learning work?

Emphasize the importance of data preprocessing in machine learning projects, detailing your experience with techniques such as cleaning, normalizing, and feature engineering. Provide an example of how preprocessing contributed to a model's success.

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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 18, 2025

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