Jobs → Engineering → MLOps Engineer

About the Role We are looking for an experienced MLOps Engineer to build, deploy, and operate production-grade ML and LLM infrastructure across cloud and on-premises environments. Key Responsibilities • Build and deploy production-grade ML and LLM infrastructure • Operate ML and LLM infrastructure across cloud and on-premises environments • Deploy ML/LLM platforms across SaaS and customer on-premises environments Requirements • 5–10 years of experience in MLOps, ML Infrastructure, or ML Platform Engineering • Strong hands-on experience with vLLM, SGLang, TensorRT-LLM, Triton, or TGI • Expertise in AWS, Azure, or GCP • Strong Kubernetes, Docker, GPU infrastructure, and model-serving experience • Python, MLflow/Kubeflow, Terraform, and CI/CD • Experience deploying ML/LLM platforms across SaaS and customer on-premises environments • Air-gapped and offline deployment experience Benefits • 12 month contract with potential for extension