MLOps Engineer

Guidehouse • Tysons, VA

1d

About The Position

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.

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

Nice To Haves

• Experience supporting the Department of Defense, including work associated with Advana or enterprise analytics platforms
• Bachelor’s degree in computer science, Engineering, Data Science, or a related technical discipline
• Experience operationalizing ML solutions that work with federal financial or budgetary data
• Hands‑on experience with Databricks, including MLflow, Spark, and Delta Lake
• Experience deploying or maintaining ML workflows in Palantir Foundry
• Familiarity with governance, compliance, and risk controls associated with AI in federal environments
• Experience in Azure (including Azure Government) or AWS GovCloud
• Knowledge of responsible AI, model risk management, or regulated ML environments
• Master’s degree in a relevant technical field

Responsibilities

• 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

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees