MLOps Engineer

🕒 May 20

⚔️ Virginia – Remote

⚔️ Virginia – Remote

💵 113k - 188k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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Guidehouse

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 2018

💰 Grant on 2023-02

Consulting • Digital Services • Public Sector

Guidehouse is a global consultancy offering advisory, digital, and managed services across commercial and public sectors. It is purpose-built to support industries such as national security, financial services, healthcare, energy, and infrastructure. Guidehouse collaborates with leaders to navigate complexity and drives transformational changes that impact the future. Their expertise spans data analytics, digital technologies, risk management, and more, with a strong emphasis on sustainability and innovation.

📋 Description

• 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

🎯 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

🏖️ 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