DevOps Engineer
Core
Own, scale, and secure cloud and on-premise computing environments for ML model training and inference.
Role type
DevOps Engineer (MLOps & GPU Infrastructure)
Builds
High-performance GPU clusters, CI/CD pipelines, and containerized ML workloads
Domain
Cloud Infrastructure & Machine Learning
Deliverable
production ML models
Required skills
GPU cluster management, Kubernetes, Terraform, Python, CI/CD pipeline design, observability, security governance
Preferred skills
LLM orchestration frameworks, cloud certifications
Technologies
NVIDIA H100/A100, CUDA/ROCm, vLLM, Triton Inference Server, GitHub Actions, GitLab CI, ArgoCD, AWS/GCP/Azure, Docker, KubeFlow, Ray, Prometheus, Grafana, OpenTelemetry, HashiCorp Vault
Responsibilities
Provision and scale GPU clusters for model training; support model deployment and inference optimization; design and maintain CI/CD pipelines; manage cloud resources via IaC; deploy and orchestrate containerized workloads; implement observability dashboards; enforce DevSecOps practices
Seniority
Mid-level, hands-on IC
