Senior MLOps Platform Architect

5+ years of experience in Senior DevOps, SRE, or MLOps roles Proven experience designing, building, and operating production Kubernetes clusters Hands-on expertise with Terraform or similar Infrastructure-as-Code tools Strong programming skills in Python or Go Experience creating and maintaining CI/CD pipelines (GitLab, Jenkins) Practical experience deploying ML models in production (ASR, TTS, NLU, LLM/Agentic AI) Familiarity with ML orchestration and model tracking tools (Kubeflow, Airflow, MLflow, SageMaker Model Registry) Experience with GPU and specialized hardware deployment Deep understanding of AWS cloud infrastructure, networking, scaling, storage, and security best practices Experience with containerization and deployment tooling (Docker, Helm) and observability stacks (Prometheus, Grafana)

Design, build, and own AWS-based MLOps infrastructure Architect and operate production Kubernetes clusters Build and maintain CI/CD pipelines for ML workloads Integrate and manage MLOps lifecycle tools Implement observability and monitoring Collaborate with ML engineers, data scientists, and researchers Establish best practices and standards for MLOps infrastructure