Description

You will build and maintain end-to-end ML operationalization pipelines in regulated cloud environments.

This role is on-site.

Responsibilities

• Design and implement MLOps architectures using Databricks on AWS GovCloud.
• Operationalize ClassicAI and GenAI ML models into production systems.
• Develop and manage ML workloads using distributed computing frameworks.
• Implement and maintain CI/CD DevOps processes for ML systems.
• Utilize AWS CloudFormation for infrastructure management.

Required Skills

• 4-6 years of experience with Python and PySpark coding.
• 4-6 years of experience with AWS GovCloud, Export Control, and FedRAMP environments.
• 4-6 years of experience with ML frameworks including Keras, TensorFlow, and PyTorch.
• 4-6 years of experience with Azure Databricks or AWS Databricks, focusing on Unity Catalog and serverless solutions.
• 4-6 years of industry experience with Spark and Kubernetes ecosystem.
• 4-6 years of experience implementing classification, clustering, optimization, deep learning, and NLP using Python.
• 4-6 years of experience with model operationalization in production.

Key Skills

Education

Any Graduate