Senior DevOps / MLOps Engineer

Senior DevOps / MLOps Engineer to support an early-stage startup building a machine learning platform on Google Cloud.

Location: any
Start: ASAP
Duration: mid-long term
Engagement:  Part-time
English: B2+

We are looking for a Senior DevOps / MLOps Engineer to support an early-stage startup building a machine learning platform on Google Cloud.

The role focuses on designing and maintaining cloud infrastructure and deployment pipelines for ML workloads, with a strong emphasis on Kubernetes (GKE) and Infrastructure as Code (OpenTofu/Terraform).

Required Experience

• 5+ years in DevOps / Platform Engineering
• Strong hands-on experience with:
  • GCP (production environments)
  • Kubernetes (preferably Google Kubernetes Engine)
  • Infrastructure as Code (Terraform or OpenTofu)
• Experience deploying and operating ML workloads in production
  • model inference (required)
  • training pipelines (basic familiarity expected)
• CI/CD experience (e.g. GitHub Actions)
• Strong understanding of:
  • containerization (Docker)
  • networking (VPC, IAM)
  • environment isolation (dev / staging / prod)

Nice to Have

• Experience with Vertex AI or similar ML platforms
• Experience with ML orchestration tools (Kubeflow, Airflow, etc.)
• Hands-on experience with GPU workloads on Kubernetes
• Familiarity with model lifecycle (versioning, artifacts, deployment)
• Experience in early-stage or fast-moving startup environments

Not a Fit If

• DevOps background without experience supporting ML workloads in production environments
• Experience limited to managed/serverless platforms without Kubernetes
• No hands-on experience with Infrastructure as Code