LMI is seeking an ML Ops Engineer to support the operationalization, sustainment, and continuous improvement of computer vision models used on autonomous edge platforms for a Special Operations customer. This role is responsible for the lifecycle management of machine learning models that operate onboard disconnected edge systems in tactical environments. This position bridges field operations, data science, and autonomy software to ensure models improve over time without degrading mission performance.

What You'll Do

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.
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.
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.
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.
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.

What We're Looking For

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.

Nice to Have

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.