Applied Machine Learning Platform Engineer
Core
Building scalable training infrastructure, data pipelines, and tooling to support computer vision model development and deployment.
Role type
Mid-level Applied Machine Learning Platform Engineer
Builds
Distributed training pipelines, data pipelines, feature stores, and ML platform infrastructure
Domain
Power grid analytics / Computer vision / Cloud infrastructure
Deliverable
infrastructure
Required skills
Python (idiomatic, async, type hints), distributed systems design, database schema design, workflow orchestration, CI/CD automation, code review, integration testing
Preferred skills
None stated
Technologies
Python, Pytest, FastAPI, Pydantic, Git, Docker, MLflow, Weights & Biases, Github Actions, AWS, GCP, Kubernetes, Helm, Terraform, postgres, DynamoDB, Bigtable
Responsibilities
Design and maintain scalable training infrastructure for computer vision workloads; Implement and manage distributed training pipelines (multi-GPU, multi-node); Build and maintain robust data pipelines for ML development; Design database schemas and storage strategies for large training datasets; Implement and manage feature stores, data versioning, and experiment tracking; Automate existing analysis workflows; Conduct code reviews and write integration tests for ML pipelines
Seniority
Mid-level, hands-on IC
