Design and maintain CI/CD pipelines for ML model training and deployment.
Manage containerized services on AWS ECS, optimizing for cost, latency, availability.
Automate infrastructure provisioning and service configuration with Terraform.
Work to maintain and scale services using third-party LLM providers.
Build data pipelines feeding models from BigQuery, S3, and DynamoDB.
Instrument services with observability tools (Datadog, OpenTelemetry, Langfuse) and set SLOs.

🎯 Requirements

2-3 years in ML Ops; 3-4 years in DevOps/CloudOps/SRE.
Strong proficiency in Python.
Hands-on experience with Docker containerization and container orchestration.
Solid understanding of CI/CD for ML workflows in production.
Experience with Infrastructure as Code, preferably Terraform.
AWS (ECS, ECR, S3, DynamoDB, CloudWatch) and GCP (BigQuery, Vertex AI).

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