Machine Learning (ML) Administrator - Sr

Nalley Consulting•Doral, FL

1d•Hybrid

About The Position

Manage machine learning model versioning, lineage tracking, and compliance with governance policies, ensuring reproducibility and secure deployment. Implement and monitor ML infrastructure, optimizing compute resource allocation across cloud and on-premises environments. Support the validation of AI/ML pipelines, ensuring models remain accurate, explainable, and aligned with operational objectives. Submit the ML Model Governance & Deployment Report, summarizing model lifecycle management, performance tracking, and security compliance.

Requirements

Master’s degree or higher (e.g., Ph.D.) in Computer Science, Information Technology, Systems Engineering, Data Science, Business Administration, Engineering Management, or a closely related field; or a minimum of 11+ years of relevant experience.
11+ years of experience managing complex technical projects in enterprise data architecture, Databricks administration, and cloud-based data platforms.
Strong background in databricks platform administration, including workspace configuration, Unity Catalog, cluster performance tuning, and cloud integration.
Strong background in data pipeline development (ETL/ELT), Delta Lake optimization, and AI/ML workflow integration.
Strong background in SysEngOps, DevSecOps, version control systems (Git), and CI/CD pipelines for automated deployment and governance.
Strong background in Cloud security, role-based access control (RBAC), and compliance with DoD data policies across AWS, Azure, and GCP.
Skilled in Databricks platform administration, including workspace management, cluster optimization, and Unity Catalog integration for secure data governance.
Proficient in ETL pipeline development, Delta Lake architecture, and data lakehouse optimization for DoD analytics and mission-critical data workflows.
Experienced in SysEngOps, DevSecOps, version control systems (Git), and CI/CD pipelines to streamline Databricks development and deployment.
Knowledgeable in identity and access management (IAM), role-based access control (RBAC), and cloud security best practices across AWS, Azure, and GCP.
Hands-on expertise in Python, SQL/NoSQL, Apache Spark, Databricks SQL, Terraform, and cloud-native data services for large-scale data processing and analytics.
Required clearance: TS/SCI

Responsibilities

Manage machine learning model versioning, lineage tracking, and compliance with governance policies, ensuring reproducibility and secure deployment.
Implement and monitor ML infrastructure, optimizing compute resource allocation across cloud and on-premises environments.
Support the validation of AI/ML pipelines, ensuring models remain accurate, explainable, and aligned with operational objectives.
Submit the ML Model Governance & Deployment Report, summarizing model lifecycle management, performance tracking, and security compliance.