Model Operations Engineer

Job Title : Model Operations Engineer

Location : Washington, D.C. (Hybrid / Remote options based on client needs)

Job Type : Contract

Pay Range : $65 $70 per hour

Work Hours : 9 AM 5 PM

Job Summary

We are seeking an experienced Model Operations Engineer to ensure the reliable deployment, operation, and optimization of machine learning models across an enterprise-scale platform. You will support the transformation toward a scalable "platform-as-a-product" environment and work closely with engineering, data science, architecture, and IT operations teams.

This role is ideal for someone who brings strong technical and analytical skills, operational rigor, and deep experience in ensuring model reliability, performance, governance, and compliance.

Key Responsibilities Model Deployment & Operationalization

Deploy, manage, and maintain machine learning models across production environments.

Ensure models meet enterprise requirements for reliability, uptime, latency, and performance.

Implement operational workflows including version control, rollback strategies, and model lifecycle automation.

Model Monitoring & Performance Optimization

Define and track key operational metrics such as drift, accuracy degradation, resource utilization, and SLA performance.

Perform root-cause analysis for model failures or inconsistencies and drive corrective actions.

Continuously improve model observability, monitoring dashboards, and alerting systems.

Platform & IT Operations Integration

Work closely with IT Operations teams on CMDB / IT Asset Management to align model assets with enterprise standards.

Ensure model environments follow network segmentation, security controls, and compliance guidelines (e.g., PCI or internal policies).

Collaborate with platform engineering to support high-availability architecture and resilient model execution.

Cross-functional Collaboration

Partner with data scientists, product managers, and engineering teams to operationalize new models and enhancements.

Translate operational needs into technical tasks, pipelines, or configuration updates.

Facilitate communication between business and technical teams regarding model performance and risks.

Agile Execution & Continuous Improvement

Participate in Agile ceremonies and work within SAFe or similar frameworks to support planned deliverables.

Contribute to the operations backlog by identifying gaps, improvements, and automation opportunities.

Analyze operational data to drive continuous improvement and platform evolution.

Qualifications

5+ years of hands-on experience in Model Operations, MLOps, Data Engineering, Platform Engineering, or related fields.

Bachelor's degree in Computer Science, Engineering, Data Science, or similar technical domain.

Strong understanding of IT operations, CMDB, asset management, networking fundamentals, and security / compliance frameworks (PCI preferred).

Experience with tools supporting Agile delivery (Jira, Confluence, Jira Align, etc.).

Strong analytical, problem-solving, and decision-making skills.

Ability to collaborate effectively with engineering, architecture, operations, and business teams.

Preferred Skills

Experience with model observability platforms (MLflow, SageMaker, Datadog, Evidently, Arize, etc.).

Experience working in highly regulated environments or with compliance-governed model workflows.

Familiarity with SAFe Agile or similar scaled frameworks.

Equal Opportunity Statement

The organization welcomes applicants of all backgrounds and abilities. Accommodations for the hiring process are available upon request.