Design, train, and validate supervised, unsupervised, and deep learning models using open-source libraries (PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM) to support forecasting, classification, anomaly detection, and NLP use cases
Conduct rigorous experiment design: feature engineering, hyperparameter tuning, cross-validation, and evaluation using appropriate metrics (precision/recall/F1, RMSE, AUC-ROC) to ensure production-quality model performance
Fine-tune and adapt open-source LLMs (LLMA, Mistral, and similar) for domain-specific tasks including document summarization, entity extraction, and question-answering over classified and unclassified networks
Develop and maintain RAG pipelines: chunking strategies, embedding model selection, retrieval evaluation, and prompt engineering to deliver high-quality LLM-augmented analytics
Applied Problem-Solving
Translate mission requirements into ML solutions: work directly with analysts, operators, and leadership to scope problems, define success criteria, and deliver models that produce actionable operational insights
Build models across multiple domains including predictive analytics (logistics, readiness), NLP/text analytics (reports, intelligence documents), anomaly detection (cybersecurity, network, behavioral), and computer vision where applicable
Design lightweight, optimized models for edge and disconnected environments when required, supporting model optimization and conversion (ONNX, TensorRT, OpenVINO) for tactical deployment
MLOps & Lifecycle (Collaborative)
Version, track, and reproduce experiments using MLflow, DVC, and Git; maintain clear documentation of model lineage, training data, and performance baselines
Package trained models for deployment in containerized environments (Docker, Kubernetes) in coordination with the platform engineering team. Ownership of deployment infrastructure is flexible and project-dependent
Integrate models into existing CI/CD pipelines, analytics platforms, and decision support tools in collaboration with the DevSecOps and data engineering teams
Data Security & Compliance
Ensure all model development adheres to DoD security, encryption, and data handling standards, including tagging, metadata management, and retention policies
Operate within classified environments (SIPR/NIPR), following cybersecurity and data stewardship protocols across air-gapped and hybrid infrastructure
Requirements
AI Frameworks, Applied Problem Solving, Data Compliance, Machine Learning Model Development Certifications:
None Experience:
8 + years of related experience US Citizenship Required:
Yes
Job Description:
Education & Experience
Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, Applied Mathematics, Data Science, or related quantitative field
8+ years of hands-on AI/ML model development experience with a strong record of delivering production models, not just prototypes
Compliant with DoD Directive 8140 (i.e., CompTIA Security + CE cert)
Active Secret clearance is required. Must be TS/SCI eligible
Must be able to work on site at MacDill AFB. Not a remote role.
Technical Skills
Strong Python proficiency and deep experience with open-source ML frameworks (PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM, Hugging Face Transformers)
Demonstrated ability to train, fine-tune, and evaluate models end-to-end-from raw data through feature engineering, model selection, training, validation, and production handoff
Experience with LLM fine-tuning techniques (LoRA, QLoRA, PEFT) and RAG architecture design (vector databases, embedding strategies, retrieval evaluation)
Working knowledge of MLOps toolchains (MLflow, DVC, Weights & Biases) and version control (Git).
Familiarity with containerized deployment (Docker, Kubernetes) in air-gapped or on-premise environments
Experience working with large-scale data systems and meda
Benefits
Vision insuranceRemote work optionsFlexible schedule
Additional Information
Type of Requisition:
Regular
Clearance Level Must Currently Possess:
Top Secret
Clearance Level Must Be Able to Obtain:
Top Secret/SCI
Public Trust/Other Required:
None
Job Family:
Data Science and Data Engineering
Job Qualifications:
General Dynamics It · Macdill Afb, FL