Job Description

We are seeking a DevOps Engineer to own, scale, and secure our cloud and on-premise computing environments. You will collaborate with ML researchers, data scientists, and software engineers to streamline model training, optimize GPU cluster utilization, and automate CI/CD pipelines. Responsibilities include AI & GPU infrastructure management (NVIDIA H100/A100, CUDA/ROCm), MLOps and model serving pipelines (vLLM, Triton Inference Server, Llama, Mistral), CI/CD and automation (GitHub Actions, GitLab CI, ArgoCD), IaC ( Terraform, Pulumi), containerization and orchestration (Kubernetes, Docker, Kubeflow or Ray), observability (Prometheus, Grafana, OpenTelemetry), and security/governance (DevSecOps, Vault, container image scanning). Qualifications include 3+ years in DevOps/SRE/Cloud/Platform Engineering with exposure to ML workloads; strong hands-on experience with AWS, GCP, or Azure and production Kubernetes/Docker; scripting in Python, Bash, or Go; mastery of Terraform, GitOps, and automated testing/deployment pipelines; familiarity with GPU provisioning and model serving runtimes. Preferred: experience with LangChain, Ray Serve, vLLM; degree in CS/CE; cloud/Kubernetes certifications (e.g., CKA, AWS/GCP DevOps Engineer).