Job description

Prescient Edge is seeking a ML Administrator to support a Federal Government client. Please note that the availability of this position is contingent upon contract award. Benefits: At Prescient Edge , we believe that acting with integrity and serving our employees is the key to everyone's success. To that end, we provide employees with a best-in-class benefits package that includes: • A competitive salary with performance bonus opportunities.  • Comprehensive healthcare benefits, including medical, vision, dental, and orthodontia coverage. • A substantial retirement plan with no vesting schedule. • Career development opportunities, including on-the-job training, tuition reimbursement, and networking. • A positive work environment where employees are respected, supported, and engaged. Description: • ML Administrator (Manage knowledge graph metadata integration, data governance, and cataloging in Databricks Unity Catalog.) • Proposed personnel possess the knowledge and capability to support Databricks platform administration and enterprise data architecture for DoD data-driven projects: 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. • Shall manage machine learning model versioning, lineage tracking, and compliance with governance policies, ensuring reproducibility and secure deployment. • Shall implement and monitor ML infrastructure, optimizing compute resource allocation across cloud and on-premises environments. • Shall submit the ML Model Governance & Deployment Report, summarizing model lifecycle management, performance tracking, and security compliance. Requirements Experience: • Minimum of 11+ years of experience managing complex technical projects in enterprise data architecture, Databricks administration, and cloud-based data platforms. • Databricks platform administration, including workspace configuration, Unity Catalog, cluster performance tuning, and cloud integration. • Data pipeline development (ETL/ELT), Delta Lake optimization, and AI/ML workflow integration. • SysEngOps, DevSecOps, version control systems (Git), and CI/CD pipelines for automated deployment and governance. • Cloud security, role-based access control (RBAC), and compliance with DoD data policies across AWS, Azure, and GCP. Education: • 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. Security clearance: • Must be a US citizen and able to obtain a clearance. Location: • Doral, Florida. (USSOUTHCOM Headquarters)

Requirements

Must-haves

Prescient Edge is seeking a ML Administrator to support a Federal Government client.
Please note that the availability of this position is contingent upon contract award.
ML Administrator (Manage knowledge graph metadata integration, data governance, and cataloging in Databricks Unity Catalog.)
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.
Shall manage machine learning model versioning, lineage tracking, and compliance with governance policies, ensuring reproducibility and secure deployment.
Shall implement and monitor ML infrastructure, optimizing compute resource allocation across cloud and on-premises environments.
Shall submit the ML Model Governance & Deployment Report, summarizing model lifecycle management, performance tracking, and security compliance.
Minimum of 11+ years of experience managing complex technical projects in enterprise data architecture, Databricks administration, and cloud-based data platforms.
Databricks platform administration, including workspace configuration, Unity Catalog, cluster performance tuning, and cloud integration.
Data pipeline development (ETL/ELT), Delta Lake optimization, and AI/ML workflow integration.
SysEngOps, DevSecOps, version control systems (Git), and CI/CD pipelines for automated deployment and governance.
Cloud security, role-based access control (RBAC), and compliance with DoD data policies across AWS, Azure, and GCP.
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.
Must be a US citizen and able to obtain a clearance.
Doral, Florida. (USSOUTHCOM Headquarters)

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Keywords to mirror

mlci/cdawsazuregcppythonsqlmachine learningai

Platform: hrsmart
Effort: medium

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