Principal/Staff Machine Learning Engineer

Fiserv

Principal/Staff Machine Learning Engineer designing and deploying scalable ML solutions for Fiserv. Collaborating with stakeholders to enhance credit risk and fraud management strategies.

Posted 5/6/2026full-timeBerkeley Heights • New Jersey, New York • 🇺🇸 United StatesLead💰 $128,000 - $216,000 per yearWebsite

Tech Stack

Tools & technologies

AWSCloudMicroservicesPython

About the role

Key responsibilities & impact

Architect and maintain the machine learning deployment framework used to operationalize models and decisioning engines.
Partner with stakeholders to define business use cases, success criteria, and project timelines, and own requirements gathering, solution design, deployment strategy, and performance tracking for data science deployments.
Design, build, and manage batch and real-time machine learning pipelines to support deployment of models, decision frameworks, and optimization engines.
Collaborate with Data and Decision Science team members to build feature libraries, feature stores, feedback loops, and reusable components that streamline model development, validation, and deployment.
Own operational governance of the model lifecycle, including model versioning, promotion, rollback, deprecation, and ongoing monitoring for production machine learning systems.
Develop and optimize cloud-based data architectures for scalability, low latency, reliability, and cost efficiency, implementing robust data quality controls, validation checks, test coverage, monitoring, and alerting for production-grade pipelines and data products.
Deploy data and analytics solutions to Amazon Web Services (AWS) using CI/CD automation and DevOps best practices, and maintain clear technical documentation while collaborating within Agile workflows using tools such as JIRA and Confluence.
Conduct analytics and support development of machine learning and predictive model pipelines and frameworks that advance credit risk and fraud strategies.

Requirements

What you’ll need

6 years of experience in machine learning engineering, data engineering, or data science, designing and building production-grade data or ML pipelines in a commercial environment.
6 years of experience developing and optimizing data solutions on cloud platforms, including hands-on experience with AWS capabilities and Snowflake in an engineering context, along with production use of machine learning pipelines, feature stores, or MLOps practices.
6 years of experience creating Python microservices, working with containers, and developing application programming interfaces (APIs) to support data and machine learning solutions.
6 years of experience collaborating with internal and external stakeholders and driving initiatives using clear, effective verbal and written communication skills.
6 years of experience building scalable, low-latency systems or feature components that support analytics, machine learning, or decisioning use cases.
6 years of experience with CI/CD automation and DevOps practices to deploy, monitor, and support data solutions in production environments.
Bachelor’s degree or higher in Mathematics, Statistics, Computer Science, Engineering, or a related quantitative field, or equivalent combination of education, related experience and/or military experience.

Benefits

Comp & perks

Fuel Your Life program to support your physical, financial, social, and emotional well-being.
Paid holidays and generous time away policies.
No-cost mental health support through Employee Assistance Programs.
Living Proof program to recognize your peers’ extra effort with points redeemable for rewards.
Eight Employee Resource Groups to foster a collaborative culture and expand your network.
Unparalleled professional growth with training, development, and internal mobility opportunities.
Medical, dental, vision, life, and disability insurance options available from day one.
Retirement planning and discounted shares with the Employee Stock Purchase Plan.
Tuition assistance and reimbursement program.
Paid parental, caregiver, and military leave.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learning engineeringdata engineeringdata scienceproduction-grade data pipelinescloud-based data architecturesPython microservicesapplication programming interfaces (APIs)CI/CD automationDevOps practicesMLOps

Soft Skills

collaborationeffective communicationrequirements gatheringsolution designperformance trackingstakeholder engagementproject managementgovernancemonitoringdocumentation