Machine Learning Operations Engineer

Job Description Summary Organization's Summary Statement: The Applied Research Laboratory for Intelligence & Security (ARLIS) at the University of Maryland is a University-Affiliated Research Center (UARC) dedicated to advancing research, innovation, and technology transition to improve decision making for U.S. national security. ARLIS combines deep scientific expertise with operational insight to address challenges in intelligence analysis, cybersecurity, artificial intelligence / machine learning, quantum science, and human-machine teaming. Researchers, scientists, engineers, and analysts at ARLIS collaborate with government agencies, industry partners, and academic institutions to deliver actionable insights and transformative solutions through research and development. Employees at ARLIS work on projects of critical importance, contribute directly to the nation’s security, and are supported by a culture that values integrity, collaboration, and professional growth. ARLIS is seeking a mid-level MLOps Engineer to support the deployment, scaling, and operationalization of machine learning systems for national security applications. This role focuses on bridging research and production by enabling robust, secure, and reproducible ML pipelines in mission-critical environments. The successful candidate will work closely with AI researchers, software engineers, and domain experts to transition advanced algorithms into operational capabilities. Key Responsibilities: -Design, build, and maintain scalable ML pipelines for training, evaluation, and deployment. -Operationalize machine learning models in secure, production-grade environments (on-prem, cloud, hybrid). -Implement CI/CD workflows for ML systems, including automated testing, validation, and monitoring. -Manage data pipelines, feature stores, and model versioning to ensure reproducibility and auditability. -Monitor model performance, drift, and system health; implement feedback loops and retraining strategies. -Collaborate with researchers to translate experimental models into production-ready systems. -Integrate security best practices into ML workflows (DevSecOps for AI systems). -Support deployment of ML systems in constrained or classified environments. -Contribute to infrastructure design supporting AI/ML workloads (GPU clusters, distributed systems). Must be able to obtain a U.S. security clearance. If selected, you must meet the requirements for access to classified information and will be subject to a government security clearance investigation that includes criminal and credit history checks, as well as verification of U.S. citizenship, birth, education, employment, and military history. Final offer is contingent upon the candidate’s ability to successfully obtain the necessary interim Secret security clearance, as determined by the U.S. Government, prior to commencing employment. Physical Demands: Sedentary work performed in a normal office environment; exerts up to 10 pounds of force occasionally and/or negligible amount of force frequently or constantly to lift, carry, push, pull or otherwise move objects, including the human body. Ability to attend meetings both on and off campus. Spending long hours in front of a computer screen. Minimum Qualifications: -Bachelor’s degree in Computer Science, Engineering, Data Science, or related field. -3–6 years of experience in software engineering, data engineering, or MLOps. -Experience with ML frameworks (e.g., PyTorch, TensorFlow) and pipeline tools (e.g., Airflow, Kubeflow). -Proficiency in Python and experience with containerization (Docker) and orchestration (Kubernetes). -Experience with cloud platforms (AWS, Azure, or GCP) and ML services. -Understanding of software engineering best practices (CI/CD, testing, version control). Preferences: -Experience deploying ML systems in regulated or security-sensitive environments. -Familiarity with data governance, model auditing, and explainability techniques. -Experience with distributed training, GPU acceleration, and large-scale data systems. -Knowledge of infrastructure-as-code (Terraform, CloudFormation). -Experience supporting national security, defense, or intelligence-related programs. -Active U.S. security clearance. Work Environment & Impact: -Work on cutting-edge AI/ML systems addressing real-world national security challenges. -Collaborate with leading experts across disciplines in a highly innovative R&D environment. -Help transition advanced research into operational capabilities with tangible mission impact. Licenses/ Certifications: N/A Additional Job Details Required Application Materials: Cover Letter, Resume, List of References Best Consideration Date: 6/26/26 Posting Close Date: N/A Open Until Filled: Yes Financial Disclosure Required No For more information on Financial Disclosure, please visit Maryland's State Ethics Commission website. Department VPR-Applied Research Lab for Intelligence & Security Worker Sub-Type Faculty Regular Salary Range $150,000 - $225.000 Benefits Summary For more information on Regular Faculty benefits, select this link. Background Checks Offers of employment are contingent on completion of a background check. Information reported by the background check will not automatically disqualify anyone from employment. Before any adverse decision, the finalist will have an opportunity to provide information to the University regarding disclosable background check information. The University reserves the right to rescind the offer of employment or otherwise decline or terminate employment if the information reported by the background check is deemed incompatible with the position, regardless of when the background check is completed. Employment Eligibility The successful candidate must complete employment eligibility verification (on Form I-9) by presenting documents that establish identity and work authorization within the timeframe required by federal immigration law, and where applicable, to demonstrate renewed employment authorization. Failure to complete employment eligibility verification or reverification within the timeframe set forth by law may result in suspension or termination of employment. EEO Statement The University of Maryland, College Park is an Equal Opportunity Employer. All qualified applicants will receive equal consideration for employment. Please read the University’s Equal Employment Opportunity Statement of Policy. Title IX Non-Discrimination Notice Resources Learn how military skills translate to civilian opportunities with O*Net Online Search Firm Managed Recruitment There are some positions that are not advertised on this career site as the search is being managed by a Search Firm. Please visit the link below to see these available opportunities: Search Firm Managed Vacancies The University of Maryland, College Park is the state's flagship university and one of the nation's preeminent public research universities. A global leader in research, entrepreneurship and innovation, the university is home to more than 40,700 students, 14,000 faculty and staff, and 388,000 alumni all dedicated to the pursuit of Fearless Ideas. Located just outside Washington, D.C., we discover and share new knowledge every day through our renowned research enterprise and programs in academics, the arts and athletics. And we are committed to social entrepreneurship as the nation’s first “Do Good” campus. EEO Statement The University of Maryland, College Park is an Equal Opportunity Employer. All qualified applicants will receive equal consideration for employment. Please read the University’s Equal Employment Opportunity Statement of Policy. Title IX Non-Discrimination Notice Resources Learn how military skills translate to civilian opportunities with O*Net Online The University works hard to make its websites accessible to any and all users. If you need assistance completing the application process, please contact us at one of the below options: Email: jobs@umd.edu Phone: 301.405.7575 Maryland Relay: Dial 711 This contact information cannot be used to inquire about application status. There are some positions that are not advertised on this career site as the search is being managed by a Search Firm. Please visit the link below to see these available opportunities: Search Firm Managed Opportunities