Data/ML Platform Engineer

Role:Architect the environment. You won't just build pipelines; you’ll build the infrastructure that allows ML Engineers and AI researchers to work at speed. Your goal is to make the platform seamless, scalable, and secure.Key Responsibilities:Manage and optimize Databricks clusters and Snowflake instances.Implement and maintain infrastructure as code (Terraform/CloudFormation) on AWS.AI Infrastructure: Set up and govern AI services like AWS Bedrock, vector databases, and agent-building platforms to empower ML teams.Ensure the platform handles high-concurrency workloads and autoscaling requirements.Must Have:Deep expertise in AWS services (S3, EC2, IAM, EKS, Bedrock).Experience managing Databricks workspaces and Snowflake administration.Strong background in Linux, Docker, and Kubernetes.Good to Have:Apache Iceberg: Hands-on experience implementing Iceberg for storage optimization and cross-tool compatibility.Experience with model serving frameworks and LLM gateway configurations.

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