AI/ML Engineer - Public Sector

• Develop evaluation and assessment tools and frameworks to measure newly developed models for performance against key metrics across a wide domain of tasks and knowledge sets
• Identify, propose, and implement modifications of existing models and model implementation frameworks to optimize for new tasks
• Lead conceptualization of both traditional and agentic implementation strategies for cloud and on-premises model deployments within broader system architectures
• Lead and optimize distributed ML workloads on multiple government cloud and non-cloud infrastructures
• Align AI/ML deployments with FedRAMP, NIST 800-53, FISMA, and DISA SRG, maintaining strict security standards
• Create reference architectures and deployment patterns to streamline ML adoption across government agencies
• Translate mission objectives into ML-focused technical specifications and project plans
• Apply advanced security controls and zero-trust architectures to protect ML pipelines and data
• Continuously assess ML workloads for performance, cost, and security improvements, driving ongoing refinement

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field. Master’s or PhD a plus
• 4+ years of experience in AI/ML engineering, MLOPS, systems architecture, or similar technical roles
• 2+ years of experience working with government networks and security requirements
• An understanding of government security frameworks (FedRAMP, NIST 800-53, FISMA, DISA SRG) and how they apply to ML workloads
• History of leading or delivering high-impact ML initiatives in enterprise or government environments
• preference for those with articulable experience assessing performance of alternative models, architectures, and implementation strategies
• A commitment to meeting the demanding engineering standards required to support national security and defense clients
• A strong interest in being at the forefront of the AI revolution
• TS Active Clearance required for the role + ability to travel
• Familiar with AWS, Azure, and/or GCP services for ML workloads
• Experience with government cloud offerings (AWS GovCloud, Azure Government, etc.)
• Multi-cloud ML architecture design and implementation
• Cloud cost optimization and resource governance for AI/ML
• Knowledge of Kubernetes administration (EKS, AKS, GKE)
• Container security and compliance for ML containers
• Experience with IaaC, such as Terraform, Ansible, Pulumi, etc., for provisioning complex ML environments
• CI/CD pipeline integration for automated ML model deployment
• Network security for ML pipelines
• Government compliance frameworks
• Security automation and continuous compliance monitoring
• Python proficiency (ML model development, data processing, pipeline orchestration)
• API design and development for ML services
• Debugging and performance optimization in ML systems
• Code review and quality assessment
• Strategic thinking and architectural vision for AI/ML initiatives
• Executive-level communication skills, especially when conveying complex ML concepts
• Technical innovation and team leadership in ML/AI settings
• Problem-solving in high-pressure mission-critical environments
• Stakeholder management across technical and non-technical audiences

Competitive compensation, equity, and benefits