Senior AI/ML Engineer - Point Mugu, CA

F3EA Inc

12h•Onsite

About The Position

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.

Requirements

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
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)

Nice To Haves

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

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