ML Ops Engineer
Core
Build and maintain reproducible training, evaluation, and CI pipelines for autonomous defense models to enable controlled, repeatable model development.
Role type
MLOps Engineer
Builds
Training and evaluation pipelines, CI/CD for ML, model registry, experiment tracking infrastructure
Domain
Defense / Autonomous Systems / Machine Learning Operations
Deliverable
infrastructure
Required skills
Python, software engineering for infrastructure, building ML pipelines, CI/CD implementation, experiment tracking, model lifecycle management
Preferred skills
wiring pipelines to on-device testing, hardware-in-the-loop testing integration
Technologies
Python
Responsibilities
Build and maintain reproducible training and evaluation pipelines; Implement CI for ML work to ensure comparable runs; Maintain a model lifecycle registry from sandbox to production; Manage experiment tracking and logging for traceability; Automate on-device and hardware-in-the-loop test runs
Seniority
Mid-level, hands-on IC
