AI/ML Engineer

This is a fully remote position, open to applicants in Alabama.

📋 Description

• Design, create, and implement AI/ML models and pipelines that achieve mission and performance goals.

• Construct, train, and refine models utilizing frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain.

• Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration).

• Implement and enhance vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid).

• Write clean and efficient Python code for data ingestion, feature engineering, embeddings, and inference services.

• Experiment with the fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT).

• Contribute to agent-based applications using frameworks such as LangGraph, AutoGen, CrewAI, or DSPy.

• Integrate AI services into real-world systems through APIs, event-driven workflows, or UI copilots.

• Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and meet customer requirements.

• Participate in peer reviews, contribute to shared repositories, and document models and experiments to ensure reproducibility.

⛳️ Requirements

• Must be a U.S. citizen and willing to obtain and maintain a security clearance, as necessary.

• 6-10+ years of professional experience in the development and deployment of AI/ML solutions in production settings.

• At least 3 years of professional experience within the Department of Defense/Department of War (DoD/DoW) focusing on AI assurance, security, and deployment environments.

• Strong Python development skills with practical experience in building AI/ML solutions.

• Direct experience with ML frameworks including PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain.

• Demonstrated ability to construct and deploy MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent technologies.

• Working knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph).

• Professional experience in fine-tuning and evaluating LLMs or smaller task-specific models using LoRA, QLoRA, or PEFT.

• Professional experience integrating AI capabilities into production systems or mission-related applications.

• Familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI, DSPy) and multi-agent reasoning.

• Understanding of prompt engineering, retrieval quality, and grounding methods.

• Exposure to GPU-based or edge inference environments.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.

• Active Secret clearance is preferred; the ability to obtain one is required.

🏝️ Benefits

• No benefits specified