MLOps Engineer

Role Overview

MLOps Engineer to build and operate ML pipelines on Google Cloud Platform (GCP). This is a remote contract role and the candidate should have experience working only on GCP.

Responsibilities

• Build and automate ML/AI pipelines across the ML lifecycle (data versioning, training, validation, deployment, and monitoring)
• Create and optimize BigQuery workloads, including scheduled queries and integration with ML pipelines
• Use GCP services to support data and streaming workflows, including:
  • GCS (data storage)
  • Pub/Sub (messaging/streaming)
  • Dataflow (data pipeline processing)
• Deploy containerized workloads using GKE or Cloud Run
• Implement automated CI/CD for ML deployments using Cloud Build (or similar)
• Manage infrastructure as code using Terraform (or Deployment Manager)
• Write automation using Python and Bash/scripting

Requirements

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

Nice to Have

• Deeper specialization in monitoring/operationalization of deployed ML systems