ML Infrastructure Engineer
Core
Design and build systems for versioning training data, generated datasets, and model artifacts with end-to-end lineage tracking; develop reliable and reproducible ML training and data-generation pipelines.
Role type
ML Infrastructure Engineer
Builds
Data versioning systems, ML training pipelines, CI/CD workflows, and model serving infrastructure
Domain
Machine Learning Infrastructure (via careerplan.io/jobs/22887-ml-infrastructure-engineer-at-mach9)
Deliverable
infrastructure
Required skills
Python, PyTorch, ML pipeline orchestration, data versioning, model serving optimization, CI/CD, infrastructure-as-code
Preferred skills
AWS, containerized ML workflows, GPU-accelerated training, large unstructured datasets
Responsibilities
Design systems for versioning training data and model artifacts; develop reproducible ML training pipelines; create CI/CD workflows with automated checks; build tooling for launching and monitoring training jobs; optimize and scale real-time model inference services; own deployment and monitoring processes for production endpoints
