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Staff Machine Learning Engineer- AI Governance - job 1 of 22

Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

AI Governance (AIG) Engineering team is part of the Data and AI Platform (DAP) technology organization in Visa. The team’s mission is to provide a Trustworthy AI – an engineering solution for Visa to achieve centralized AI excellence across Visa. We aim to develop, assess and deploy AI systems in a responsible and trustworthy way at Visa. This is a fantastic opportunity to join the effort undergoing in building the AI Observatory product for Visa. The AI Observatory product provides an inventory of ML models and AI systems, oversight for model’s full lifecycle, and governance of all model’s accuracy, transparency, fairness, and robustness. We are also uplifting domain-specific models to the unified AI Governance framework and streamline the modeling efforts to a centralized AI excellence across Visa.

As an AI Engineer in AI Governance engineering team, you will have the unique chance to make a direct and meaningful impact by building and delivering solutions that power AI Governance engineering solution. You will design, enhance, and build solutions dealing with the next generation AI/ML and Generative AI technology and be an agent of transformation.  We deliver and support strategic goals and have a lasting impact on our enterprise. We aim to stay ahead of the curve adapting to the advancement of Generative AI and keep our business miles ahead of our competitors.   

Responsibilities

  • You will design, develop, and maintain scalable and reliable AI governance service.
  • You will apply robust architectural principles to create effective and efficient solution.
  • You will work closely with interdisciplinary teams, including data scientists, product managers, and legal experts, to ensure compliance of AI systems with ethical standards and regulatory requirements.
  • You will be instrumental in developing an advanced Responsible AI platform utilizing the latest Generative AI technology.
  • You will address the evolving challenges in AI governance, ensuring the creation of responsible and trustworthy AI solutions.
  • You will investigate and assess emerging technologies and third-party solutions, prototyping and strategizing their integration within Visa.

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 three days a week, Tuesdays, Wednesdays and Thursdays with a general guidepost of being in the office 60% of the time based on business needs.

Qualifications

Basic Qualifications:

  • 5 or more years of relevant work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD.

Preferred Qualifications:

  • 6 or more years of work experience with a Bachelors Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD
  • Sound knowledge about AI Governance, Generative AI, and Trustworthy AI highly preferred.
  • Experience in software development, big data, and machine-learning processes.
  • Experience in all phases of development - the design, coding, testing, debugging, deployment, and monitoring of applications highly preferred.
  • Experienced with high-performance imperative languages including Python, Java, Golang, React.js, Next.js, full-stack web development.
  • Built predictive models using Python and ML libraries and managed their lifecycle, from development to production.
  • Experienced Big data and distributed computing platforms such as Hadoop, Spark, Docker, Kubernetes, and Airflow.

Additional Information

Work Hours: Varies upon the needs of the department.

Travel Requirements: This position requires travel 5-10% of the time.

Mental/Physical Requirements: This position will be performed in an office setting.  The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.

Visa is an EEO Employer.  Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.  Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.

U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is 155,300.00 to 225,300.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.

Average salary estimate

$190300 / YEARLY (est.)
min
max
$155300K
$225300K

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 Staff Machine Learning Engineer- AI Governance, Visa

Join Visa as a Staff Machine Learning Engineer in AI Governance and become a part of a dynamic team dedicated to fostering responsible and trustworthy AI systems. Located in the vibrant Foster City, California, Visa is a forefront leader in payments and technology, handling a staggering 259 billion transactions annually across the globe. As a core member of the AI Governance Engineering team within our Data and AI Platform organization, you’ll be instrumental in guiding and developing the AI Observatory product, aimed at ensuring compliance and ethical standards for AI systems. This role allows you to design and maintain scalable AI governance services while applying robust architectural principles to craft effective solutions. You’ll collaborate with an interdisciplinary team, including data scientists and legal experts, to integrate advanced Generative AI technologies into our Responsible AI platform. If you’re passionate about machine learning, AI governance, and making a meaningful impact in a major global enterprise, this position at Visa could be your next career move. Not only will you address the emerging challenges in AI governance, but you’ll also help Visa maintain its competitive edge in the fast-evolving world of AI. This hybrid position strikes a balance between remote work and office collaboration, allowing you to creatively contribute to strategic goals while enjoying a flexible work arrangement. Ready to connect the world through innovation? Apply today for the Staff Machine Learning Engineer role in AI Governance at Visa, and be part of an uplifting and transformative mission!

Frequently Asked Questions (FAQs) for Staff Machine Learning Engineer- AI Governance Role at Visa
What are the key responsibilities of a Staff Machine Learning Engineer in AI Governance at Visa?

In the role of Staff Machine Learning Engineer in AI Governance at Visa, you'll be responsible for designing, developing, and maintaining scalable AI governance services. You'll work closely with interdisciplinary teams, ensuring compliance of AI systems with ethical standards while investigating emerging technologies that can enhance our AI governance framework. Your role will also focus on integrating advanced Generative AI technologies to create responsible and trustworthy solutions.

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What qualifications are required for the Staff Machine Learning Engineer position at Visa?

To qualify for the Staff Machine Learning Engineer position in AI Governance at Visa, candidates should have a minimum of 5 years of relevant experience paired with a Bachelor's degree, or at least 2 years with an Advanced degree. Preferred candidates will have a strong background in AI Governance, Generative AI, and software development, along with expertise in languages such as Python and Java, and experience in big data platforms like Hadoop and Spark.

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How does the role of Staff Machine Learning Engineer contribute to AI Governance at Visa?

The Staff Machine Learning Engineer role is pivotal in advancing AI Governance at Visa by developing the AI Observatory product, which oversees the entire lifecycle and governance of machine learning models and AI systems. This ensures that our AI solutions are accurate, transparent, fair, and robust, ultimately driving responsible AI usage within the organization.

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What technologies will I work with as a Staff Machine Learning Engineer at Visa?

As a Staff Machine Learning Engineer in AI Governance at Visa, you will work with a variety of cutting-edge technologies. This includes generative AI technologies, big data platforms like Spark and Hadoop, and machine learning libraries. You will also have opportunities to work with high-performance languages like Python and Java, as well as project management and orchestration tools like Docker and Airflow.

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What kind of team will I be working with at Visa as a Staff Machine Learning Engineer?

In this role at Visa, you will be collaborating with a diverse and interdisciplinary team. This team includes data scientists, product managers, and legal experts, all working together toward building and ensuring compliance for AI systems. This collaborative environment will provide opportunities for shared learning and innovation in the field of AI governance.

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Common Interview Questions for Staff Machine Learning Engineer- AI Governance
What experience do you have with AI governance principles?

When asked about experience with AI governance principles, outline specific frameworks or standards you have used in the past. Discuss how you ensured compliance with ethical guidelines and how you have assessed AI models for fairness and transparency. Providing examples of past projects will strengthen your response.

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Can you describe a time you developed an AI model from start to finish?

To effectively answer this question, detail your involvement in one or more phases of model development: from ideation, design, and coding to testing and deployment. Highlight tools and methodologies you used, especially within big data contexts or predictive modeling, to show your depth of experience.

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How do you approach collaboration with cross-functional teams?

Emphasize the importance of communication and adaptability in your approach to collaboration. Provide examples where you successfully worked with data scientists, legal teams, or product managers. Mention specific tools or practices that helped facilitate effective teamwork.

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What strategies do you use to keep up with advancements in AI technology?

Discuss multiple methods you leverage to stay informed about AI advancements, such as attending conferences, participating in webinars, reading research papers, or engaging in online communities. This not only shows your commitment to personal development but also your proactive approach to applying new technologies.

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What challenges have you faced when implementing AI solutions?

Respond by identifying specific challenges, such as ethical concerns, compliance issues, or technical limitations. Explain how you addressed these challenges with practical solutions, emphasizing your problem-solving skills and ability to adapt.

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Describe your experience with programming languages relevant to AI and ML.

Be prepared to share your proficiency in languages such as Python, Java, or Scala. Mention specific libraries or frameworks you've utilized for machine learning and any projects where you implemented these skills successfully in real-world applications.

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How do you ensure a model's accuracy and reliability?

Outline your approach to model validation and testing procedures. Discuss metrics you use to assess accuracy and how you manage model updates over time to maintain performance. Including your experience with A/B testing can add value to your answer.

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What do you know about Visa's mission regarding AI?

Demonstrate your understanding of Visa's commitment to innovation and responsible technology by discussing how their mission aligns with your own values. Share insights on how AI can enhance the payment ecosystem responsibly, maintaining trust and security.

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How would you handle discrepancies found in AI models?

When addressing discrepancies, talk about your problem-solving approach—how you would diagnose the issue, involve relevant team members, and apply solutions for correction. Emphasize the importance of transparency and integrity in AI governance.

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What excites you most about working in AI governance at Visa?

Express genuine enthusiasm for the role by discussing your passion for ethical AI, technology's potential, and Visa's influential position in the financial sector. Reflect on your commitment to making a positive impact through your work in AI governance.

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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 19, 2025

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