MLOps Engineer

This is a fully remote position, open to applicants in Virginia.

📋 Description

• In the role of MLOps Engineer, you will be responsible for designing, implementing, and supporting platforms, pipelines, and operational processes that facilitate scalable, secure, and reliable deployment of machine learning solutions for federal clients.

• You will collaborate closely with data scientists, AI engineers, data engineers, and government stakeholders to operationalize models throughout development, testing, and production environments.

• Your contributions will be pivotal in enabling secure AI and ML delivery within DoD and federal financial sectors, ensuring that models are repeatable, auditable, and compliant with federal standards.

• You will design, construct, and maintain comprehensive MLOps pipelines that support model training, testing, deployment, monitoring, and retraining.

• Your role will involve implementing CI/CD workflows for ML models and data pipelines within secure federal environments.

• You will operationalize machine learning models developed by data science teams, ensuring they are ready for production.

• Responsibilities include developing and managing model versioning, artifact management, and experiment tracking.

• You will implement monitoring solutions for model performance, drift, data quality, and the overall health of pipelines.

• Automating infrastructure provisioning and deployment using infrastructure-as-code and DevOps best practices will be part of your duties.

• You will support the auditability, explainability, and governance of AI/ML systems.

• Collaborating with stakeholders to align MLOps architectures with mission needs and security requirements will be essential.

⛳️ Requirements

• US Citizenship is required.

• An ACTIVE and MAINTAINED "SECRET" Federal or DoD security clearance is necessary.

• A Bachelor’s degree is required.

• You should have 3–5 years of experience in MLOps, ML engineering, data engineering, DevOps, or similar technical roles.

• Strong proficiency in Python and ML tooling for model packaging, deployment, and monitoring is essential.

• Hands-on experience in constructing CI/CD pipelines for data and ML workloads is required.

• Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes, or their managed equivalents) is necessary.

• Experience working within secure cloud or hybrid environments for federal or DoD clients is expected.

• Knowledge of ML lifecycle management concepts, including versioning, reproducibility, and monitoring, is important.

• The ability to collaborate with both technical and non-technical teams and clearly communicate complex system designs is essential.

🏝️ Benefits

• Medical, Rx, Dental & Vision Insurance

• Personal and Family Sick Time & Company Paid Holidays

• Position may be eligible for a discretionary variable incentive bonus

• Parental Leave and Adoption Assistance

• 401(k) Retirement Plan

• Basic Life & Supplemental Life

• Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts

• Short-Term & Long-Term Disability

• Student Loan PayDown

• Tuition Reimbursement, Personal Development & Learning Opportunities

• Skills Development & Certifications

• Employee Referral Program

• Corporate Sponsored Events & Community Outreach

• Emergency Back-Up Childcare Program

• Mobility Stipend