AI / ML Engineer

DEPLOY's Client's Cyber Works and Digital Engineering teams in Huntsville, Alabama  design, build, and integrate emerging AI/ML technologies to harden and secure the systems that defend the nation, across ground, missile defense, space, and installation infrastructure S&T programs. We're expanding our Secure AI practice to build and assure trusted, robust AI/ML solutions that interpret complex datasets, predict outcomes, and automate decision-making in support of critical military platforms. This is a consolidated announcement covering multiple tracks; your assignment may emphasize one or a blend of: Classic ML & Predictive Modeling, LLM/GenAI Applications, AI Assurance & Responsible AI, Edge AI/ML Deployment, and hardening AI/ML systems against adversarial threats. All tracks require independent research, cross-functional collaboration, and the ability to clearly communicate complex technical work to stakeholders. Core Responsibilities: Design, develop, and maintain machine learning models, from classical algorithms (regression, tree ensembles, clustering) to modern deep learning architectures. Build LLM-enabled applications and retrieval-augmented generation (RAG) pipelines, including vector embedding generation, vector database integration, and prompt/context engineering. Develop AI assurance and evaluation tooling: robustness testing, bias/fairness analysis, model traceability, red-team/adversarial testing, and audit artifact generation. Optimize and deploy models for production and edge environments (quantization, compression, containerized inference, ONNX/TensorRT). Implement secure model and data pipelines, defend against adversarial ML threats, and ensure supply-chain integrity (SBOM) for AI components. Conduct data processing/analysis to improve model accuracy; document and present development processes and assurance evidence to stakeholders. Contribute to Agile, team-based planning and estimating in a fast-paced, collaborative environment. Minimum Requirements: Bachelor's degree or equivalent experience in CS/CPE/EE/Data Science (or related field). Proven experience in one or more: ML/LLM development, assurance/evaluation tooling, or deploying edge computing solutions. Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. Proficiency in Python and at least one additional language (Java, C++). Strong understanding of data structures, data modeling, and software architecture. Highlighted Skills & Experience: Modern AI: LLM frameworks and application development; vector embeddings and vector databases; RAG architectures; prompt/context engineering; LLM fine-tuning; model evaluation and benchmarking. Classic ML: Feature engineering, model selection/tuning, statistical analysis, and predictive modeling across structured and unstructured data. AI Assurance: Responsible AI practices (robustness, bias/fairness, traceability); adversarial ML defenses; red-team testing; auditability…