ML Ops Engineer - Clearance Required

Overview

ML Ops Engineer - Clearance Required.

Location:

US-NC-Fort Bragg. This role supports the operationalization, sustainment, and continuous improvement of computer vision models used on autonomous edge platforms for a Special Operations customer. The position manages the lifecycle of machine learning models operating onboard disconnected edge systems in tactical environments to keep models accurate, testable, versioned, and safely deployable without requiring operators to be AI experts. It bridges field operations, data science, and autonomy software to improve models over time without degrading mission performance or introducing unsafe behavior.

This position requires an active Secret clearance.

LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. We bring commercial-grade platforms and mission-ready AI to federal agencies at commercial speed, serving defense, space, healthcare, and energy sectors.

• Solution Design: Design the ML lifecycle for computer vision models operating on edge platforms.
• Establish model versioning, validation, and deployment patterns suitable for disconnected tactical environments.
• Develop guardrails to ensure autonomy behavior remains predictable and auditable.
• Create architectures for collecting operational data and feeding it back into retraining pipelines.
• Development: Build and maintain pipelines for model packaging, testing, and deployment to edge systems.
• Implement automated testing to ensure new models do not degrade performance.
• Develop repeatable processes so operators can update systems without ML expertise.
• Integrate data science outputs into fieldable, supportable software packages.
• Testing and Quality Assurance: Validate model performance against real operational data.
• Conduct regression testing to ensure updated models maintain or improve detection and tracking performance.
• Ensure traceability of which model versions were used during specific operations.
• Maintenance and Support: Support field units in updating and maintaining onboard models.
• Troubleshoot issues related to model performance and deployment in operational environments.
• Continuously improve processes for safe model iteration and deployment.
• Documentation: Create technical documentation for model lifecycle processes.
• Develop operator-friendly guides for updating and validating onboard systems.
• Document model versioning, testing results, and deployment procedures.

• Experience implementing ML Ops practices for computer vision or edge autonomous systems.
• Understanding of model versioning, validation, and deployment pipelines.
• Experience working with disconnected or bandwidth-constrained environments.
• Familiarity with containerization and packaging of ML models for deployment.
• Understanding of how to translate data science outputs into operational software.
• Strong problem-solving and analytical skills.
• Ability to work independently and as part of a team.
• Excellent communication and interpersonal skills.
• Must possess an active Secret clearance.
• Preferred Qualifications:
• Experience with autonomous systems, robotics, or unmanned platforms.
• Experience supporting Special Operations or tactical technology programs.
• Familiarity with computer vision model development and evaluation.
• Experience designing data pipelines for model retraining from field-collected data.
• Understanding of responsible AI principles and human-in-the-loop autonomy systems.

Salary information:
The target salary range for this position is $140,. The salary range displayed represents typical range and is not a guarantee of compensation. Individual salaries are determined by various factors including location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.

LMI is an Equal Opportunity Employer. LMI is committed to the fair treatment of all hiring and employment practices, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, pregnancy, disability, age, protected veteran status, citizenship status, genetic information, or any other characteristic protected by applicable federal, state, or local law. If you are a person with a disability needing assistance with the application process, please contact accommodations