Senior Machine Learning Engineer (Applied Intelligence)
Core
Bridge ML research and production operations by building robust datasets, training infrastructure, and inference systems for factory floors.
Role type
Senior Machine Learning Engineer (MLOps & Production Infrastructure)
Builds
Production-grade ML systems, data pipelines, and inference frameworks for manufacturing environments
Domain
Defense manufacturing / Industrial IoT / MLOps
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, Docker, Kubernetes, Data pipeline orchestration, Model versioning, Observability, Time-series data handling
Preferred skills
Edge compute deployment, OT network integration, MLOps component standardization
Technologies
Kubernetes, Docker, PyTorch, TensorFlow, Vector databases, Feature stores
Responsibilities
Own production hardening and deployment of ML prototypes; Build and maintain inference infrastructure across cloud and on-premises OT; Implement monitoring, alerting, and drift detection systems; Coordinate with data engineering and manufacturing teams; Architect end-to-end ML platform stack; Manage dataset creation, curation, and lifecycle governance
Seniority
Senior, hands-on IC
