ChatGPT Jobs · 22 hours ago
AI/ML Engineer
Frontier Technology Inc. (FTI) is seeking a hands-on AI/ML Engineer to design, build, and deploy advanced machine learning solutions supporting defense and national security missions. This role focuses on execution in oversight, ideal for an engineer who thrives in the code, enjoys building end-to-end pipelines, and takes pride in seeing their work directly impact operational systems.
Computer Software
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
Qualification
Required
Must be a U.S. citizen and be willing to obtain and maintain a security clearance, as needed
6-10+ years of professional experience developing and deploying AI/ML solutions in production environments
Professional experience within the Department of Defense (DoD/DoW) AI assurance, security, and deployment 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)
Professional experience 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 applications
Preferred
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 preferred; ability to obtain one is required
Company
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Funding
Current Stage
Early StageCompany data provided by crunchbase