DevOps with Python 8648 G
Core
Build and expand a Kubernetes-based inference benchmarking framework for end-to-end performance measurements, cross-cloud comparisons, and model test scenarios.
Role type
Senior DevOps Engineer (MLOps & Benchmarking)
Builds
Automated benchmarking frameworks, dashboards, and reporting pipelines for ML inference performance.
Domain
Cloud Infrastructure + MLOps + Performance Engineering
Deliverable
production ML models
Required skills
Kubernetes (GKE), Python, Observability, GCP services, MLOps, Autoscaling, CI/CD
Preferred skills
AWS, Azure
Technologies
Kubernetes, GKE, GCS, Cloud Monitoring, GitHub Actions, vLLM, HPA, Metrics Server, Cluster Autoscaler
Responsibilities
Provide platform-wide performance signals for inference workloads, deliver standardized cross-cloud benchmarking, support leadership reporting with cloud performance results, enable team validation of new features via unified frameworks, extend benchmarking coverage for latency and scale-out, integrate automated benchmarking APIs and dashboards, collaborate on reusable inference components.
Seniority
Senior, hands-on IC
