MLOps Engineer

Role Overview

MLOps Engineer (Senior) to build and operate ML platforms on Google Cloud Platform (GCP). This is a remote contract role with a strong focus on end-to-end MLOps and hands-on GCP experience only.

Responsibilities

• Implement MLOps/ML engineering workflows across the ML lifecycle: data versioning, training, validation, deployment, and monitoring.
• Build and automate data and model pipelines using BigQuery, GCS, Pub/Sub, and Dataflow.
• Integrate GCP services with ML pipelines, including scheduled/optimized BigQuery SQL and orchestrating data movement.
• Deploy and run containerized workloads using GKE or Cloud Run.
• Automate CI/CD and deployments using Cloud Build (or similar CI/CD tooling).
• Manage infrastructure using Terraform (or Deployment Manager).

Requirements

• 15+ years of experience (strong senior resources).
• Hands-on GCP-only MLOps/DevOps/ML engineering experience.
• Strong Python skills.
• Comfortable with Bash/scripting for automation.
• Proficiency with BigQuery: writing and optimizing SQL, scheduled queries, and integrating with ML pipelines.
• Experience with GKE or Cloud Run.
• Experience with Cloud Build or similar CI/CD tools.
• Familiarity with Terraform or Deployment Manager.
• Experience with GCS, Pub/Sub, and Dataflow.
• Familiarity with ML frameworks: TensorFlow, PyTorch, scikit-learn.

Nice-to-haves

• Strong ownership of production ML monitoring and operational best practices.
• Deep familiarity with ML platform data lineage and reproducibility via data versioning.