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Machine Learning Engineer, Staff

Calling all innovators - find your future at Fiserv.

We're Fiserv, a global leader in Fintech and payments, and we move money and information in a way that moves the world. We connect financial institutions, corporations, merchants and consumers to one another millions of times a day - quickly, reliably, and securely. Any time you swipe your credit card, pay through a mobile app, or withdraw money from the bank, we're involved. If you want to make an impact on a global scale, come make a difference at Fiserv.

Job Title

Machine Learning Engineer, Staff

What does a successful Staff Machine Learning Engineer do at Clover?

The Data Science team at Clover is responsible for improving the merchant experience by building AI and machine learning (ML) powered features into Clover products.  The team builds both AI/ML applications as well as the underlying AI/ML platform architecture required to scale these experiences.

As a successful Staff Machine Learning Engineer, you will own and drive the architecture design, development, and deployment for all AI/ML products the Data Science team develops for Clover merchants.

What you will do:

  • Leverage your extensive AI/ML architectural design and development experience to build and deploy end-to-end, performant, customer-facing AI/ML applications

  • Research state-of-the-art AI/ML techniques to incorporate into the team’s best practices/design patterns

  • Collaborate directly with Product, Design, and Engineering counterparts on shaping the AI/ML roadmap, user experience, and technical infrastructure

  • Provide technical leadership, guidance, mentorship to other members of the team

What you will need to have:

  • 5+ years of industry experience developing end-to-end customer-facing AI/ML applications and infrastructure

  • Strong fluency in Python, REST APIs, and AI/ML frameworks, modeling techniques, and model serving

  • Experience with data stores (relational (e.g. MySQL, Snowflake), NoSQL (e.g.MongoDB, Redis), object (e.g. GCS), vector databases), Ci/CD (Docker, Jenkins), serverless (Cloud Run/Functions)

  • Strong, internally motivated  mindset to improve the team’s capabilities in a rapid, iterative, thoughtful, and empathetic manner

  • Effective communication skills to convey complex concepts in a concise manner in written, visual, and verbal form to both technical and non-technical, leadership audiences

What would be great to have:

  • Advanced degree in a quantitative discipline: Machine Learning. Artificial Intelligence, Computer Science, Statistics, Mathematics, Physics or equivalent

#LI-JI1

#LI-Onsite

Salary Range

$124,300.00 - $213,100.00

These pay ranges apply to employees in New York and California. Pay ranges for employees in other states may differ.

It is unlawful to discriminate against a prospective employee due to the individual's status as a veteran.

Thank you for considering employment with Fiserv.  Please:

  • Apply using your legal name
  • Complete the step-by-step profile and attach your resume (either is acceptable, both are preferable).

Our commitment to Equal Opportunity:

Fiserv is proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, gender, gender identity, sexual orientation, age, disability, protected veteran status, or any other category protected by law. 

If you have a disability and require a reasonable accommodation in completing a job application or otherwise participating in the overall hiring process, please contact AskHR.US@fiserv.com. Please note our AskHR representatives do not have visibility to your application status. Current associates who require a workplace accommodation should refer to Fiserv’s Disability Accommodation Policy for additional information.

Note to agencies:

Fiserv does not accept resume submissions from agencies outside of existing agreements. Please do not send resumes to Fiserv associates. Fiserv is not responsible for any fees associated with unsolicited resume submissions.

Warning about fake job posts:

Please be aware of fraudulent job postings that are not affiliated with Fiserv. Fraudulent job postings may be used by cyber criminals to target your personally identifiable information and/or to steal money or financial information. Any communications from a Fiserv representative will come from a legitimate Fiserv email address.

Average salary estimate

$168700 / YEARLY (est.)
min
max
$124300K
$213100K

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 Machine Learning Engineer, Staff, Fiserv

Hey there! If you've got a passion for artificial intelligence and machine learning, then being a Staff Machine Learning Engineer at Fiserv in sunny Sunnyvale, California might just be your dream job! At Fiserv, we're all about moving money and information seamlessly, and we pride ourselves on being a global leader in Fintech. Imagine being part of the Data Science team at Clover, where you'll engage in innovative projects that enhance the merchant experience through cutting-edge AI and ML features. You're not just designing products; you're creating the architecture that will scale these experiences for millions of users! In this role, you'll leverage your expertise to develop and deploy high-performance, customer-facing AI applications, while collaborating with Product, Design, and Engineering teams to drive our AI/ML roadmap. Whether it's incorporating state-of-the-art techniques or mentoring team members, your impact will be felt throughout the organization. If you have over five years of industry experience with AI/ML applications, a strong command of Python, and a knack for effective communication, we want to hear from you! Join us at Fiserv and be part of a team that's defining the future of financial technology. Your journey to making a difference starts here!

Frequently Asked Questions (FAQs) for Machine Learning Engineer, Staff Role at Fiserv
What are the key responsibilities of a Staff Machine Learning Engineer at Fiserv?

As a Staff Machine Learning Engineer at Fiserv, your primary responsibilities include designing, developing, and deploying customer-facing AI/ML applications that enhance the merchant experience. You'll need to leverage your extensive architectural design experience and collaborate with other departments to shape the AI/ML roadmap and user experience.

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What qualifications are needed for the Staff Machine Learning Engineer position at Fiserv?

To qualify for the Staff Machine Learning Engineer role at Fiserv, you should have at least five years of industry experience in developing end-to-end AI/ML applications. Strong fluency in Python and familiarity with various data stores, CI/CD tools, and serverless architectures are also crucial.

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What technologies should a Staff Machine Learning Engineer be familiar with at Fiserv?

A successful Staff Machine Learning Engineer at Fiserv should be well-versed in Python programming, REST APIs, and various AI/ML frameworks. You should also have experience with both relational and NoSQL databases, as well as CI/CD pipelines involving tools like Docker and Jenkins.

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How does collaboration work for the Staff Machine Learning Engineer at Fiserv?

Collaboration at Fiserv for the Staff Machine Learning Engineer entails working closely with Product, Design, and Engineering teams. This teamwork is essential in shaping the AI/ML roadmap and ensuring that the user experience is optimized in every project you undertake.

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What career growth opportunities exist for a Staff Machine Learning Engineer at Fiserv?

At Fiserv, a Staff Machine Learning Engineer has numerous opportunities for career growth, including the potential to take on technical leadership roles, mentor junior engineers, and influence the strategic direction of AI/ML initiatives within the company.

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Common Interview Questions for Machine Learning Engineer, Staff
Can you explain the end-to-end process of building an AI/ML application?

When answering this question, outline the steps involved in an AI/ML project such as defining the problem, data collection, preprocessing, model selection, training, validation, and deployment. Highlight your experience in each stage.

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How do you ensure the performance and scalability of AI/ML applications?

Discuss the importance of model architecture, optimization techniques, cloud computing resources, and how to monitor application performance post-deployment to ensure scalability and user satisfaction.

Join Rise to see the full answer
What are some common challenges you’ve faced when developing AI/ML products?

Share specific challenges such as data quality issues, model accuracy, and integration with existing systems. Discuss how you overcame these challenges and what you learned from the experience.

Join Rise to see the full answer
How would you approach collaborating with non-technical teams for an AI project?

Emphasize the importance of clear and concise communication. Describe how you would tailor your explanations depending on the audience's technical background and how you would work together to align on project goals.

Join Rise to see the full answer
What is your experience with various machine learning frameworks?

Detail your experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn. Provide examples of projects where you've used these frameworks and the results you achieved.

Join Rise to see the full answer
Can you describe a project where you mentored a junior engineer?

Talk about a specific instance where you guided a junior engineer through the project lifecycle. Discuss the techniques you employed to support their growth and how it benefited the project.

Join Rise to see the full answer
How do you stay updated with the latest trends in AI and ML?

Share your methods for staying informed, such as subscribing to reputable journals, attending conferences, participating in online courses, or being part of professional networks. Highlight specific recent trends you've found impactful.

Join Rise to see the full answer
What techniques do you use for data preprocessing?

Explain various preprocessing techniques like normalization, encoding categorical variables, and handling missing data. Provide examples of projects where these techniques improved model performance.

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How do you handle model validation and tuning?

Discuss approaches like k-fold cross-validation, grid search, or random search for hyperparameter tuning. Mention how you've implemented these methods in past projects for model optimization.

Join Rise to see the full answer
How would you explain a complex AI concept to a non-technical audience?

Describe how you break down complex concepts using analogies and simple language. Emphasize tailoring your communication style to the audience's level of understanding for effective engagement.

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DATE POSTED
April 15, 2025

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