ML Ops Engineer (AWS GovCloud Databricks) - Remote - W2 only

Summary: The ML Ops Engineer (AWS GovCloud Databricks) role is a remote position focused on leveraging AWS GovCloud environments and Databricks for machine learning operations. The position requires extensive experience in data engineering, machine learning, and operationalizing ML models in production. Candidates should possess strong programming skills in Python and PySpark, along with familiarity with various ML frameworks. The role emphasizes collaboration with remote and global teams to deliver effective solutions.

Key Responsibilities:

• Utilize AWS GovCloud environments and Databricks for machine learning operations.
• Operationalize machine learning models in production environments.
• Collaborate with remote and global teams on data engineering and machine learning projects.
• Implement end-to-end MLOps architecture and monitor Lakehouse solutions.
• Engage in CICD DevOps processes for efficient deployment.

Key Skills:

• Bachelor's degree in computer science, Engineering, Applied Mathematics or related field.
• 4 to 6 years of experience with AWS Gov Cloud environments and Export Control FedRAMP environments.
• 8 to 10 years of experience in data engineering and machine learning.
• 4 to 6 years of experience with machine learning topics including classification, clustering, optimization, and deep learning NLP using Python.
• 6 to 8 years of experience in Python and PySpark coding.
• 4 to 6 years of experience with ML frameworks such as Keras, Tensorflow, PyTorch, and HuggingFace.
• 4 to 6 years of experience with ClassicAI GenAI ML Model Operationalization.
• 4 to 6 years of experience in Azure Databricks and AWS Databricks.
• 4 to 6 years of experience with distributed computing frameworks like Spark and Kubernetes.
• 4 to 6 years of experience with CICD DevOps processes.
• Effective communication skills.

Salary (Rate): undetermined

City: undetermined

Country: USA

Working Arrangements: remote

IR35 Status: outside IR35

Seniority Level: undetermined

Industry: IT