AI/MLOps Lead

Job Description

Job Description

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We are a growing information technology company that offers its employees a culture of success, the chance to work on revolutionary federal IT infrastructure, and the opportunity to grow alongside cutting-edge technology that is reshaping the industry. We are seeking forward-thinking candidates that have strong experience in operational support and can help take to the next level in a proactive stance.

Chameleon Integrated Services has expertise in operations management, quality systems, data operations and cybersecurity. We secure some of the most sensitive data for the Department of Defense and for other U.S. federal government agencies. We are known for the great care we take with clients and employees, and we believe in promoting from within.

We offer a Full Benefits package including:

• Competitive Employee Health Insurance options including dental
• 100% company paid vision plan
• 401K plan with generous company match and no vesting period
• 100% company paid life insurance
• 100% company paid long and short-term disability insurance
• Training allowance
• PTO and more

AI/ML / MLOps Lead

Location: Linthicum Heights, MD
Employment Type: Full-Time / Contingent Upon Contract Award
Clearance Required: TS/SCI clearance eligibility preferred;
U.S. Citizenship required

Position Note
Chameleon Integrated Services is actively bidding on a proposal to provide Cyberspace Operations and Development for the Enterprise (CODE) services under the DC3 Technical, Analytical, and Business Operations (TABO) requirement. This position is contingent upon contract award.

Position Overview
Chameleon Integrated Services is seeking a hands-on AI/ML and MLOps Lead to drive our technical solution and bridge a key corporate capability gap. This role requires a production-focused machine learning engineering leader rather than an academic researcher or a high-level AI strategist.
The ideal candidate will have a proven track record of taking models completely out of development sandboxes and successfully deploying, monitoring, and governing them inside live, operational, and highly regulated federal environments.

Responsibilities

• Provide hands-on technical leadership across the entire machine learning lifecycle, including use-case analysis, data-readiness assessments, and validation testing.
• Direct and execute comprehensive data preparation tasks, encompassing complex data cleaning, transformation, and custom feature engineering.
• Perform systematic model evaluations, mathematical selections, algorithmic training, and precise performance tuning against defined mission metrics.
• Orchestrate the production deployment of validated models into operational hybrid-cloud and on-premises environments.
• Establish automated continuous monitoring systems to track model health, performance metrics, and data drift over time.
• Implement and enforce strict version control, documentation standards, and rigorous DevSecOps/MLOps governance controls across all operational AI assets.
• Ensure all developed artificial intelligence models strictly adhere to agency-wide data governance policies and enterprise architecture baselines.

Required Skills & Qualifications

• Demonstrated hands-on engineering experience managing the full end-to-end ML lifecycle from initial business problem through live operational deployment.
• Practical engineering experience handling backend data preparation, structural validation, and feature-engineering pipelines.
• Proven capability setting up automated MLOps tracking mechanisms, performance monitoring, and model drift alerting systems.
• Strong understanding of version-control workflows, containerized model deployment, and DevSecOps pipeline integrations.

Preferred Qualifications

• Prior experience delivering federal, DoD, or highly regulated/classified data science and AI solutions into active production.
• Active TS/SCI security clearance.

“We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status”

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