Description

You will own the design and maintenance of end-to-end MLOps pipelines, covering data ingestion, feature engineering, model training, deployment, and monitoring.

Responsibilities

• 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, ensuring governance and security compliance.
• Handle security patching, cost optimization, and 24x7 on-call rotations for critical services.

Required Skills

• 4.5+ years of experience in MLOps or DevOps.
• Hands-on experience with AWS MLOps, SageMaker (Pipelines, Model Registry, Studio), EMR, and OpenSearch (kNN/vector search).
• Proficiency in Python and Bash scripting for CI/CD, provisioning, and monitoring.
• Experience with FastAPI or Spring Boot web services running on Linux servers (Solr/OpenSearch).
• Familiarity with AWS services including S3, DynamoDB, Lambda, and Step Functions, with a focus on cost control.
• Experience with databases such as MySQL and MongoDB.
• Hands-on expertise in ML tools like MLFlow, Airflow, or Metaflow.

Key Skills

Education

Any Graduate