ML Administrator

RemoteMidMLOpsposted 8mo ago

✦Role summaryAI-generated

This ML Administrator will oversee scalable federated data ecosystems for DoD missions, ensuring model reproducibility, governance compliance, and real-time interoperability across cloud and on-prem environments. The role demands expertise in bridging operational gaps for dynamic data integration and mission-critical AI/ML pipeline validation.

About this role

**This position is contingent upon award of contract**

SOSi is seeking an ML Administrator to support mission requirements for a structured approach to further develop, integrate, and sustain a scalable, federated data ecosystem that enhances interoperability, governance, and mission-driven analytics for a DoD customer. The primary objective of the program is to bridge the operational gaps between DoD, IC, interagency, and non-traditional international partners to enable real-time information sharing, dynamic data integration, and mission-tailored analytical capabilities.

Essential Job Duties:

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.
Validation of AI/ML pipelines, ensuring models remain accurate, explainable, and aligned with operational objectives.
Manage ML Model Governance & Deployment Reporting including summarizing model lifecycle management, performance tracking, and security compliance.

Qualifications

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 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 management, workspace configuration, cluster optimization, cluster performance tuning, and Unity Catalog integration for secure data governance.
ETL/ELT pipeline development, Delta Lake architecture and optimization, and data lakehouse optimization for DoD analytics and mission-critical data workflows.
AI/ML workflow integration within Databricks environments.
SysEngOps and DevSecOps practices with version control systems (Git) and CI/CD pipelines for streamlined Databricks development, automated deployment, and governance.
Identity and access management (IAM), role-based access control (RBAC), cloud security best practices, and compliance with DoD data policies across AWS, Azure, and GCP.
Hands-on expertise in Python, SQL/NoSQL databases, Apache Spark, Databricks SQL, Terraform, and cloud-native data services for large-scale data processing and analytics.
Knowledge and capability to support Databricks platform administration and enterprise data architecture for DoD data-driven projects and mission-critical workflows.