R&D Engineer Sr.

Title: R&D Engineer Sr.

Location: St. Paul, MN

Duration: 12 Months

100% Onsite Role Overview We are seeking a Senior Engineer to lead data operations and model evaluation activities supporting AI/ML development in a medical device environment. This role is responsible for managing the collection, organization, quality, governance, and distribution of clinical and field-derived datasets (e.g., TEE, CT, MRI, ICE imaging and AF mapping) used for AI model training and validation.

The engineer will establish and maintain ground truth datasets, evaluate model performance against reference standards, generate metrics and performance reports, and partner closely with AI/ML engineers to continuously improve model quality. The role also serves as a key liaison between clinical partners, data providers, AI development teams, Cybersecurity, Privacy, Legal, and external vendors to ensure high-quality data pipelines and compliant handling of sensitive healthcare data.

What You Will Do AI Data Management & Operations

• Manage the lifecycle of training, validation, and testing datasets used for AI/ML development.
• Coordinate collection, ingestion, organization, reviews, and maintenance of clinical and field-derived datasets, including imaging, mapping, and procedural data.
• Develop and maintain data inventories, metadata standards, lineage documentation, and tracking systems.
• Maintain auditable records of dataset provenance, versioning, approvals, and usage to support development, quality, and regulatory activities.
• Coordinate secure transfer and compliant handling and sharing of sensitive data and approved datasets with internal teams and external collaborators.
• Monitor data quality, completeness, consistency, and readiness for AI development activities.
• Support annotation and labeling workflows, including vendor management and quality review processes.
• Collaborate with AI/ML, software, systems, clinical, quality, regulatory, cybersecurity, privacy, legal, and OEC teams.
• Drive continuous improvement in data operations infrastructure and AI evaluation methodologies.
• Define and monitor data quality KPIs including completeness, consistency, annotation quality, and dataset representativeness.
• Identify data gaps and drive remediation plans with data providers and development teams.

Model Evaluation & Validation

• Establish and maintain ground truth datasets for model training and performance assessment.
• Own the governance, quality, and traceability of ground truth datasets used for training, validation, and verification activities.
• Design and execute model evaluation workflows to compare new AI models against established performance baselines.
• Coordinate with cross-functional teams to establish application-specific measures to evaluate and communicate model performance.
• Analyze failure modes, data quality issues, and performance gaps to identify improvement opportunities.
• Create dashboards, reports, and visualizations to communicate model performance trends to technical and non-technical stakeholders.
• Collaborate with AI/ML engineers to recommend improvements to data pipelines, labeling quality, and model development processes.
• Support statistical analysis and performance characterization for research, product development, and regulatory activities.

Required Qualifications

• Bachelor’s degree (or equivalent experience) in a related field (Computer Science, Engineering, Data/Analytics, Health Informatics, Biomedical, or similar).
• 5+ years of relevant industry experience
• Experience supporting AI/ML development, data engineering, model validation, analytics, or algorithm development.
• Demonstrated experience designing and executing model evaluation and performance frameworks.
• Experience with Power BI, Tableau, Azure Data Platform, Databricks, or cloud-based analytics environments.
• Demonstrated experience coordinating data transfers, documentation, or data pipeline handoffs across multiple stakeholders.
• Demonstrated ability to independently lead data operations programs with minimal supervision.
• Excellent communication skills with customers, data owners, compliance, and legal.
• Strong organizational and execution skills: tracking, follow-up, issue triage, status reporting, and escalation management.
• Demonstrated ability to lead cross-functional initiatives and influence technical decisions.

Preferred Qualifications

• Experience with medical imaging datasets including DICOM, CT, MRI, Ultrasound, TEE, ICE, or electrophysiology mapping systems.
• Experience with AI/ML model development lifecycles and MLOps workflows.
• Familiarity with machine learning evaluation methodologies and statistical validation techniques.
• Experience supporting regulated medical device software or AI-enabled products.
• Familiarity with FDA, MDR, or other regulatory expectations related to AI/ML validation.

Consultants Eligible Benefits Upon Waiting Period

• Medical and Prescription Drug Plans
• Dental Plan
• Vision Plan
• Health Savings Account (for High-Deductible Health Plans)
• Flexible Spending Accounts (Health, Limited Purpose, Dependent Care, Commuter Parking and Commuter Transit)
• Supplemental Life Insurance
• Short Term Disability (coverage varies by state)
• Long Term Disability
• Critical Illness, Hospital coverage, Accident Insurance
• MetLife Legal, MetLife ID Fraud, and MetLife Pet Insurance
• 401(k)