As an MLOps Engineer, you will design, implement, and support the platforms, pipelines, and operational processes that enable scalable, secure, and reliable deployment of machine learning solutions for federal clients.
You will partner closely with data scientists, AI engineers, data engineers, and government stakeholders to operationalize models across development, testing, and production environments.
You will play a critical role in enabling secure AI and ML delivery within DoD and federal financial environments, ensuring models are repeatable, auditable, and compliant with federal standards.
Design, build, and maintain end‑to‑end MLOps pipelines, supporting model training, testing, deployment, monitoring, and retraining
Implement CI/CD workflows for ML models and data pipelines in secure federal environments
Operationalize machine learning models built by data science teams and ensure production readiness
Develop and manage model versioning, artifact management, and experiment tracking
Implement monitoring solutions for model performance, drift, data quality, and pipeline health
Automate infrastructure provisioning and deployment using infrastructure‑as‑code and DevOps best practices
Support auditability, explainability, and governance of AI/ML systems
Collaborate with stakeholders to align MLOps architectures with mission needs and security requirements

US Citizenship required
An ACTIVE and MAINTAINED "SECRET" Federal or DoD security clearance.
Bachelor’s degree obtained.
3–5 years of experience in MLOps, ML engineering, data engineering, DevOps, or related technical roles
Strong experience with Python and ML tooling supporting model packaging, deployment, and monitoring
Hands‑on experience building CI/CD pipelines for data and ML workloads
Experience with containerization and orchestration (e.g., Docker, Kubernetes, or managed equivalents)
Experience working with secure cloud or hybrid environments supporting federal or DoD clients
Familiarity with ML lifecycle management concepts including versioning, reproducibility, and monitoring
Ability to work across technical and non‑technical teams and communicate complex system designs clearly

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

MLOps Engineer

Key skills