MLOps Engineer

Job Family:

Travel Required:

Clearance Required:

What You Will Do:

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.

Key responsibilities include:

• 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

What You Will Need:

• 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

What Would Be Great to Have:

• 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

What We Offer:

Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace.

Benefits include:

• 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

About Guidehouse

Guidehouse is an Equal Opportunity Employer–Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation.

Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco.

If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1-571-633-1711 or via email at RecruitingAccommodation@guidehouse.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation.

All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains including @guidehouse.com or guidehouse@myworkday.com.  Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse.  Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process.

If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse’s Ethics Hotline. If you want to check the validity of correspondence you have received, please contact recruiting@guidehouse.com. Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant’s dealings with unauthorized third parties.

Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.