Senior Engineer-Devops, Machine Learning Operations

WHAT YOU’LL DO Design and maintain end-to-end MLOps pipelines for data ingestion, feature engineering, model training, deployment, and monitoring.Productionize ML/GenAI services, collaborating with data scientists on model serving and workflow optimization.Implement monitoring, alerting, and observability to reduce MTTR and ensure production reliability.Manage data/feature stores and search infrastructure for scalable ML inference.Automate CI/CD for ML models and infrastructure with governance and security compliance.Handle security patching, cost optimization, and 24x7 on-call rotations for critical services.Coordinate cross-functionally with development, QA, ops, and data teams to innovate build/deployment processes. WHAT YOU’LL NEED 4.5+ years (Sr Engineer)/7+ years (Module Lead) in AWS MLOps with hands-on SageMaker (Pipelines, Model Registry, Studio), EMR, OpenSearch (kNN/vector search).Python/Bash scripting for CI/CD, provisioning, monitoring of FastAPI/Spring Boot web services; and Linux servers (Solr/OpenSearch).AWS services (S3, DynamoDB, Lambda, Step Functions) with cost control, reporting; databases (MySQL, MongoDB).Strong Linux and networking fundamentals;Hands-on expertise in ML tools (MLFlow, Airflow, Metaflow, ONNX). EXPERIENCE- MLOps Sr. Engineer, DevOps - 4.5+ years