
Senior Product Owner – Machine Learning
Mitek Systems
full-time
Posted on:
Location Type: Remote
Location: Spain
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Salary
💰 €48,000 - €60,000 per year
Job Level
About the role
- Own and manage the backlog for ML-driven biometric and document verification capabilities.
- Translate fraud, identity, and customer requirements into clear and actionable ML work items.
- Partner closely with ML engineers and data scientists to refine problem statements into feasible deliverables.
- Define acceptance criteria that reflect real world performance, not just offline model metrics.
- Serve as the primary product owner for ML and data science teams.
- Participate actively in model design discussions, prioritization, and tradeoff analysis.
- Challenge scope, timelines, and modeling approaches when misaligned with business or risk objectives.
- Propose alternate ideas across data strategy, modeling approaches, workflow design, or deployment patterns.
- Support model lifecycle activities including training, evaluation, deployment, and retraining.
- Ensure monitoring, drift detection, and feedback loops are incorporated into delivery plans.
- Help define rollout, experimentation, and rollback guardrails.
- Partner with agent operations and data teams on labeling strategy and data quality.
- Help define labeling schemas and workflows to support effective model training.
- Identify risks related to label noise, bias, or insufficient coverage across geographies and document types.
- Incorporate fraud patterns and adversarial thinking into backlog prioritization.
- Ensure features and models are resilient to evolving attack vectors such as spoofs, deepfakes, and injection attacks.
- Support layered and defense in depth approaches rather than single model dependency.
- Work closely with engineering, fraud, compliance, legal, and customer teams.
- Support internal and external conversations where ML behavior or performance needs explanation.
- Translate technical constraints into clear delivery expectations for non technical stakeholders.
Requirements
- Seven or more years of experience in product ownership, product management, or equivalent delivery focused roles.
- Demonstrated experience supporting ML based products in production.
- Direct experience working with data science and ML engineering teams.
- Strong working knowledge of computer vision and ML fundamentals.
- Experience with biometric technologies such as face matching, liveness detection, and spoof prevention.
- Experience with document verification, document classification, or document fraud detection.
- Hands-on experience building ML based products in the biometric and document identity space is highly valuable.
- Ability to evaluate tradeoffs between different modeling and data approaches without being a data scientist.
- Comfortable pushing back on ML teams when solutions are over engineered, misaligned, or not production ready.
- Able to propose alternate approaches grounded in data availability, fraud realities, and delivery constraints.
- Strong attention to detail and a bias toward shipping reliable and measurable capabilities.
- Able to clearly articulate ML concepts, risks, and tradeoffs to non technical stakeholders.
- Comfortable supporting customer facing or internal discussions around model behavior and limitations.
- Able to document requirements and acceptance criteria with precision.
Benefits
- Wellness: Universal, supplemental, and private healthcare plan choices based on country specifics
- Financial future: retirement/pension plan contributions, MTK stock plan participation
- Income protection: life event & disability coverage
- Paid time off: generous annual leave, company holidays, volunteer time off
- Learning: e-learning license, tuition reimbursement, hackathons
- Home office setup allowance
- Additional/optional benefits: pet insurance, identity theft protection, legal assistance
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningbiometric technologiesdocument verificationcomputer visionmodel designdata strategymodel lifecycle activitieslabeling schemasfraud detectionadversarial thinking
Soft Skills
product ownershipcommunicationattention to detailproblem-solvingstakeholder managementtradeoff analysiscollaborationcritical thinkingdecision makingarticulation of technical concepts