Hybrid AI/ML Engineer

at FTI - Frontier Technology Inc.

• Job title: AI/ML Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Python, PyTorch, Scikit-Learn, Tensorflow
• Location requirements: Hybrid, Dallas, United States

About the role

• AI/ML Engineer designing and deploying advanced machine learning solutions for defense and national security missions. Focused on execution and building end-to-end pipelines.

Responsibilities

• Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives.
• Build, train, and fine-tune models using 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 optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid).
• Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services.
• Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT).
• Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy.
• Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots.
• Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and aligned with customer needs.
• Participate in peer reviews, contribute to shared repositories, and document models and experiments for reproducibility.

Requirements

• Must be a U.S. citizen and be willing to obtain and maintain a security clearance, as needed.
• 4–6 years of professional experience developing and deploying AI/ML solutions in production environments.
• Strong Python development skills with hands-on experience building AI/ML solutions.
• Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain.
• Proven ability to build and deploy MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent.
• Working knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph).
• Familiarity with DoD/IC AI assurance, security, and deployment environments.
• Experience fine-tuning and evaluating LLMs or smaller task-specific models using LoRA, QLoRA, or PEFT.
• 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.
• Experience integrating AI capabilities into production systems or mission applications.
• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field.
• Active Secret clearance preferred; ability to obtain one required.

Benefits

• Telecommute
• No clearance requirements