Senior MLOps Engineer

Own the model lifecycle by designing, building, and maintaining robust ML infrastructure for training, inference, and deployment. You’ll manage Kubernetes-based environments for LLMs and speech models, using AWS/Azure/GCP and Infrastructure-as-Code for reproducible, secure operations. Build automated MLOps pipelines and CI/CD for high-throughput serving, observability, reliability, and cost optimization. Collaborate with ML researchers and mentor engineers while documenting and improving processes.