ML Administrator

About the Role

The role entails day-to-day management of ML infrastructure, optimization of compute resource allocation, and validation of AI/ML pipelines. You will also be responsible for managing ML model governance and deployment reporting, including summarizing model lifecycle management, performance tracking, and security compliance.

The team you will be working with is a dynamic group of professionals who are passionate about delivering cutting-edge technology solutions to support national security missions. As an ML Administrator, you will play a key role in helping the team achieve its objectives and contribute to the company's mission.

What You Will Do

• Manage machine learning model versioning, lineage tracking, and compliance with governance policies
• Implement and monitor ML infrastructure, optimizing compute resource allocation across cloud and on-premises environments
• Validate AI/ML pipelines, ensuring models remain accurate, explainable, and aligned with operational objectives
• Manage ML model governance and deployment reporting, including summarizing model lifecycle management, performance tracking, and security compliance
• Develop and maintain ETL/ELT pipelines, Delta Lake architecture, and data lakehouse optimization for DoD analytics and mission-critical data workflows
• Integrate AI/ML workflows within Databricks environments
• Implement SysEngOps and DevSecOps practices with version control systems and CI/CD pipelines for streamlined Databricks development, automated deployment, and governance
• Manage identity and access management, role-based access control, cloud security best practices, and compliance with DoD data policies across AWS, Azure, and GCP
• Collaborate with cross-functional teams to ensure successful deployment of ML models and infrastructure

What We Are Looking For

• Master's degree or higher in Computer Science, Information Technology, Systems Engineering, Data Science, Business Administration, Engineering Management, or a closely related field
• Minimum of 11+ years of experience managing complex technical projects in enterprise data architecture, Databricks administration, and cloud-based data platforms
• Hands-on expertise in Python, SQL/NoSQL databases, Apache Spark, Databricks SQL, Terraform, and cloud-native data services
• Knowledge and capability to support Databricks platform administration and enterprise data architecture for DoD data-driven projects and mission-critical workflows
• Experience with cloud security best practices, identity and access management, and compliance with DoD data policies
• Strong understanding of data governance, compliance, and security in the DoD sector

Nice to Have

• Experience with machine learning model development and deployment
• Knowledge of DevSecOps practices and CI/CD pipelines
• Familiarity with cloud-based data platforms and data lakehouse architecture

Benefits and Perks

• Competitive salary and benefits package
• Opportunity to work on cutting-edge technology and support national security missions
• Collaborative and dynamic work environment
• Flexible remote work arrangements
• Professional development and training opportunities
• Access to cutting-edge technology and tools

• Develop a strong portfolio showcasing your experience with machine learning model development and deployment, as well as your expertise in Databricks administration and cloud security.
• Highlight your understanding of data governance, compliance, and security in the DoD sector, and be prepared to discuss your experience with cloud security best practices and identity and access management.
• Familiarize yourself with the company's mission and values, and be prepared to discuss how your skills and experience align with the company's objectives.
• Be prepared to discuss your experience with DevSecOps practices and CI/CD pipelines, and how you have implemented these practices in previous roles.
• Research the company's technology stack and be prepared to discuss your experience with relevant tools and technologies, such as Python, Apache Spark, and Terraform.
• Be prepared to discuss your experience working in a remote team environment, and how you stay connected and collaborative with colleagues in a virtual setting.