Role Overview

MLOps Engineer to help build and operate machine learning pipelines and deployment infrastructure.

Responsibilities

Own and improve MLOps/ML Engineering workflows across the ML lifecycle (data versioning, training, validation, deployment, monitoring)
Build and optimize data and analytics pipelines (including BigQuery SQL and scheduled queries) and integrate them with ML pipelines
Deploy and run containerized workloads using GKE or Cloud Run
Set up automated build and deployment using Cloud Build (or similar CI/CD tooling)
Implement infrastructure as code using Terraform or Deployment Manager
Work with GCS, Pub/Sub, and Dataflow to construct data pipelines

Hands-on experience with MLOps, DevOps, or ML Engineering
Strong GCP experience
Strong Python skills and comfort with Bash/scripting for automation
Proficiency with BigQuery (writing/optimizing SQL, scheduled queries) and integrating it with ML pipelines
Experience with GKE or Cloud Run
Experience with Cloud Build or similar CI/CD tools
Familiarity with Terraform or Deployment Manager
Understanding of GCS, Pub/Sub, Dataflow for pipeline construction
Familiarity with ML frameworks: TensorFlow, PyTorch, scikit-learn