Senior AI/ML Engineer

Job Summary

F3EA is seeking a Senior AI/ML Engineer to support the Blue Water Instrumentation (BWI) RDT&E Tranche 1 Development and Knowledge Management team at the Point Mugu Sea Range. This role is responsible for designing, developing, and deploying AI/ML models, automated data pipelines, and intelligent process automation solutions within CMMC-compliant MS365 GCC High, Azure Government (AzureGov), and DoD enclave environments (NMCI/FlankSpeed).

The Senior AI/ML Engineer will architect and implement AI-Driven Instrumentation (AIDI) capabilities including automated data collection planning, processing, analysis, and decision-aid tools supporting RDT&E events. Beyond instrumentation, this role will develop AI-enabled solutions for business and staffing processes, including intelligent document processing, workforce analytics, predictive staffing models, and natural language interfaces leveraging Azure OpenAI Service, Copilot Studio, and Power Platform AI Builder within GCC High boundaries.

This position requires deep expertise in building production ML systems within FedRAMP High / IL4-IL6 environments, understanding the unique constraints of GCC High tenant boundaries, and ensuring all AI/ML workloads comply with DoD AI ethics principles and applicable cybersecurity requirements.

Roles and Responsibilities

• Design, develop, train, and deploy AI/ML models for AIDI capabilities including telemetry data analysis, automated collection planning, anomaly detection, predictive maintenance for prototype systems, and decision-aid tools supporting RDT&E events
• Architect and implement end-to-end ML pipelines in Azure Government (AzureGov) using Azure Machine Learning, Azure Cognitive Services, and Azure OpenAI Service within IL4/IL5/IL6 boundaries as appropriate
• Develop AI-enabled business process automation solutions within MS365 GCC High using Copilot Studio, Power Platform AI Builder, Power Automate, and SharePoint Premium (Syntex) for intelligent document processing, metadata extraction, and content classification
• Build and maintain data ingest/ETL pipelines supporting AIDI R&D objectives, including telemetry capture/replay tools, labeling workflows, data governance, and role-based access controls for experiment data (CDRL A013)
• Develop predictive workforce analytics, staffing optimization models, and intelligent scheduling tools to support program staffing and business processes
• Implement Retrieval-Augmented Generation (RAG) architectures and knowledge base solutions using Azure AI Search and Azure OpenAI within GCC High for program knowledge management and operational decision support
• Design and deliver dashboards, Common Operational Picture (COP) views, and data visualization artifacts as R&D deliverables for evaluation by Government stakeholders
• Ensure all AI/ML workloads comply with DoD AI Ethics Principles (Responsible AI), NIST AI Risk Management Framework, and applicable cybersecurity controls for the R&D test environment
• Implement model versioning, experiment tracking, and reproducibility infrastructure (MLflow, Azure ML Experiments) to support RDT&E repeatability and transition decision-making
• Collaborate with cybersecurity personnel to ensure AI/ML infrastructure meets RMF, STIG, and continuous monitoring requirements scaled to developmental use
• Support data and model traceability documentation sufficient for RDT&E repeatability, Government technical reviews, and transition decisions
• Author and contribute to technical documentation including model cards, algorithm descriptions, data dictionaries, and performance characterizations (CDRL A006)
• Stay current on emerging AI/ML techniques, DoD AI initiatives (CDAO, Task Force Lima guidance), and GCC High service availability for AI workloads

Supervisory Responsibilities

• None. May provide technical leadership and mentorship to junior data engineers and analysts.

Required Qualifications and Education

• Bachelor’s degree in Computer Science, Data Science, Machine Learning, Mathematics, or related field (Master’s preferred)
• 8+ years of experience in AI/ML engineering, data science, or applied machine learning, with at least 3 years in DoD or Federal environments
• Demonstrated experience building and deploying ML models in Azure Government or equivalent FedRAMP High cloud environments
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers)
• Experience with Azure Machine Learning, Azure Cognitive Services, and/or Azure OpenAI Service
• Hands-on experience with data pipeline engineering (Apache Spark, Azure Data Factory, Databricks, or equivalent)
• Working knowledge of MS365 GCC High capabilities and constraints, including Power Platform AI Builder, Copilot Studio, and SharePoint Premium
• Understanding of DoD Cloud SRG impact levels (IL4/IL5/IL6) and their implications for AI/ML workloads
• Experience with containerized model deployment (Docker, Kubernetes, Azure Container Instances)
• Familiarity with CMMC 2.0, NIST SP 800-53, and cybersecurity compliance requirements for development environments
• Strong understanding of data governance, PII/CUI handling, and role-based access control in classified or controlled environments
• Excellent analytical, problem-solving, and technical communication skills
• U.S. citizenship required
• Active DoD Secret clearance required; TS/SCI eligibility preferred

Required Certifications

• One or more of the following (or equivalent demonstrated expertise):
  • Azure AI Engineer Associate (AI-102) or Azure Data Scientist Associate (DP-100)
  • AWS Machine Learning Specialty or equivalent cloud ML certification
  • CompTIA Security+ CE (or higher, to satisfy DoD 8140 baseline if applicable)

Preferred Qualifications and Education

• Experience with Azure OpenAI Service in GCC High / Government tenants
• Familiarity with CDAO (Chief Digital and AI Office) guidance, DoD AI Ethics Principles, and Responsible AI frameworks
• Experience with NIST AI Risk Management Framework (AI RMF)
• Experience building RAG architectures with Azure AI Search in Government environments
• Familiarity with IRIG-106 telemetry data formats and T&E range data standards
• Experience with real-time or streaming ML inference for sensor/telemetry data
• Knowledge of NMCI and FlankSpeed environments and their development constraints
• Experience with MLOps practices: MLflow, model registries, automated retraining pipelines
• Familiarity with Power Platform governance and DLP policies in GCC High
• Experience supporting FMS (Foreign Military Sales) program data handling requirements
• Additional certifications: Azure Solutions Architect Expert, Databricks Certified, TensorFlow Developer Certificate

Physical Demands/Work Environment

• Combination of office and laboratory
• Direct, hands-on support to users and operational systems
• May require support during test events or extended operational hours