Description

You will manage machine learning operationalization within AWS GovCloud and regulated environments.

Responsibilities

• Design and implement end-to-end MLOps architectures using Databricks Unity Catalog and Mosaic AI.
• Deploy and operationalize Classic AI, Gen AI, and machine learning models in production.
• Build and maintain data pipelines using PySpark and distributed computing frameworks.
• Manage CI/CD and DevOps processes within the Kubernetes ecosystem.
• Collaborate with remote, global, and cross-functional teams to deliver ML solutions.

Required Skills

• 8 to 10 years of experience in data engineering, machine learning, and data science.
• 4 to 6 years of experience in AWS GovCloud, Export Control, and FedRAMP environments.
• 6 to 8 years of professional Python and PySpark coding experience.
• 4 to 6 years of experience with Keras, TensorFlow, PyTorch, HuggingFace Transformers, and scikit-learn.
• 4 to 6 years of experience with Azure Databricks and AWS Databricks, including Lakehouse monitoring and serverless solutions.
• 4 to 6 years of experience with Spark and Kubernetes.
• 4 to 6 years of experience in machine learning topics including classification, clustering, optimization, deep learning, and NLP.
• 4 to 6 years of experience with CI/CD and DevOps processes.
• Any Graduate degree.

Key Skills

Education

Any Graduate