Sr. Model Governance Engineer
Description
Mitek (NASDAQ: MITK) is a global leader in digital & biometric identity authentication, fraud prevention, and mobile deposit solutions. Our verified identity platform and advanced image capture solutions are built on the latest advancements in biometric recognition, artificial intelligence, computer vision and machine learning, and trusted by over 7,500 organizations worldwide. We are headquartered in San Diego, California, with operations in the United Kingdom, Spain, France, Mexico, and the Netherlands. Visit us at www.miteksystems.com.
At Mitek, we believe that teams are more resilient, effective, and innovative when they benefit from a wide range of ideas, lived experiences, and perspectives. The strength of our organization is deeply rooted in the people who power it. We know that a workforce reflecting the richness of our communities and customers helps us better serve their needs. These lived experiences influence our decisions, shape our products, services, and help us grow with intention. When it comes to talent, our goal is clear: to discover exceptional individuals and to ensure they discover us. We prioritize drive, skill, experience, and ambition in everything we do for our clients.
We are Virtual 1st! Whether you choose to work remotely from your home office or in-person from one of Mitek’s offices, our practices, processes and tools are designed to enable your success. At Mitek, the Future of Work is about flexibility and preference wherever and whenever we are working.
As a Sr. Model Governance Engineer, you will help to ensure that AI/ML models are developed, deployed, and monitored in a controlled, transparent, and compliant manner. This role partners closely with engineering, data science, risk, compliance, and product teams to support strong model governance practices and keep models audit ready.
What You Will Do (Essential Responsibilities)
Maintain the enterprise model inventory, including model owners, purpose, risk rating, and deployment status Apply model risk ratings and confirm required governance steps are completed Coordinate model release approvals, evidence collection, and sign off processes Manage versioning, archiving, and traceability for models and related documentation Ensure models have complete and standardized documentation, such as Model Cards Document model intent, assumptions, limitations, and known risks Capture explainability considerations and any human in the loop processes used Maintain data lineage and dataset information for training, validation, and monitoring Ensure required validation evidence is available, including performance and testing results Support stress testing or review activities for higher risk models Help set up and support ongoing model monitoring activities Trigger governance reviews when model, data, or scope changes occur Partner with engineering, data science, risk, compliance, and governance teams Produce clear and consistent governance documentation for both technical and non-technical audiences Support the preparation and review of datasets used for model testing and validation Support or participate in governance reviews, validations, or review meetings
What You Will Need (Required Knowledge, Skills & Abilities)
Bachelor’s degree, or higher, in a technical or quantitative field (Computer Science, Engineering, Statistics, Mathematics, or similar) Knowledge, skills and abilities typically gained through 5+ years of experience in model governance, model validation, analytics, or related engineering roles Experience managing model documentation, approvals, controls, or lifecycle tracking Understanding of AI/ML models and how they are developed, tested, and used Familiarity with model validation concepts and benchmarking approaches Working knowledge of programming languages such as Java and Python Familiarity with common data formats such as CSV and JSON Experience writing or reviewing SQL and querying databases, including working with datasets for testing or validation Understanding of application development concepts and software development lifecycles Familiarity with SDKs, APIs, and integration patterns used in production systems Experience working with or supporting systems deployed on cloud platforms (e.g., AWS, Azure, or GCP) Ability to review technical implementations to understand how models are built, deployed, and monitored Experience using documentation or tracking tools to support governance, review, or audit activities Awareness of data privacy and security considerations when working with model data and datasets
What Would be Nice (Preferred Skills & Experience)
Experience supporting models used in fraud, risk, or decisioning systems is a plus Knowledge of regulatory or governance expectations related to model risk is a plus
Who You Are (Soft Skills & Attributes)
Clear communicator, who can explain complex technical topics simply Confident presenter, able to share information to various types and levels of stakeholders Able to work across multiple teams and stakeholders Detail ‑ oriented with a strong focus on documentation and accuracy, paired with the ability to identify gaps or issues Comfortable working in risk ‑ aware and regulated environments Organized and methodical in how you manage work and information Proactive and comfortable taking ownership of governance tasks
What We Offer You (Why Join Us?)
Flexible hours with the possibility to work full remote (in the US) or from our San Diego office. You'll be able to share feedback to shape and drive innovation using the latest technologies. Opportunities to contribute to a highly diverse, inclusive an Agile native ecosystem. Training and development opportunities in a fast-growing industry. Highly competitive salary + bonus, perks and benefits. A fun and inclusive work environment where teams succeed together.