Role Overview
Support the full lifecycle of computer vision models deployed on autonomous edge platforms for tactical operations. This position focuses on building robust, maintainable systems that allow field teams to safely update and validate models without relying on constant connectivity or deep AI knowledge.
Key Responsibilities
- Design and manage end-to-end ML workflows tailored for edge-based computer vision applications
- Implement version control, testing, and deployment strategies that function reliably in offline or low-bandwidth settings
- Build safeguards that ensure autonomous behavior remains consistent, explainable, and compliant with operational standards
- Develop data feedback loops to capture real-world performance and support retraining efforts
- Construct automated pipelines for packaging, validating, and deploying models to field systems
- Ensure new model versions do not reduce accuracy or reliability through structured regression testing
- Create clear, repeatable procedures so non-specialist operators can confidently manage updates
- Turn experimental model outputs into stable, supportable software releases
- Verify model behavior using real operational data and document outcomes
- Maintain records linking model versions to specific missions or deployments
- Provide technical support to field units during model updates and troubleshooting
- Improve deployment safety and efficiency through iterative process refinement
- Produce detailed technical documentation and user-focused guides for model management
Required Qualifications
- Proven experience applying ML Ops practices to computer vision or autonomous edge systems
- Strong grasp of model versioning, validation frameworks, and deployment pipelines
- Background working in environments with limited or no network connectivity
- Experience containerizing and packaging ML models for real-world deployment
- Ability to convert research-grade models into field-ready software components
- Skilled in problem solving and data analysis
- Capable of working both independently and collaboratively
- Clear, effective communication with technical and non-technical stakeholders
- Active Secret clearance required
Preferred Qualifications
- Work history with robotics, unmanned systems, or autonomous platforms
- Involvement in Special Operations or tactical technology initiatives
- Knowledge of computer vision model development and evaluation metrics
- Experience designing data collection systems for model retraining
- Understanding of ethical AI practices and human oversight in autonomous systems
