> Markdown version of [/jobs/ext/925160-ai-ml-engineer](https://www.wearedevelopers.com/jobs/ext/925160-ai-ml-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Engineer - **Company:** Frontier Technology LLC - **Location:** Tempe, AZ, United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Software Deployment, Feature Engineering, Data Ingestion, Pytorch, Large Language Models, Multi-Agent Systems, Prompt Engineering, Deep Learning, Generative AI, SC Clearance, Scikit Learn, Kubernetes, Information Technology, HuggingFace, Machine Learning Operations, Virtual Agents - **Published:** June 8, 2026 - **Apply:** https://www.dice.com/job-detail/876d4375-52cd-4550-bc69-02961f8e1078 ## About the Role * 6 10+ years of professional experience developing and deploying AI/ML solutions in production environments. * Minimum 3 years of experience within DoD/Defense AI assurance, security, and deployment environments. * Strong programming expertise in Python. * Hands-on experience with: * PyTorch * TensorFlow * Scikit-learn * Hugging Face * LangChain * Experience building and deploying MLOps pipelines using: * MLflow * Kubeflow * DVC * Equivalent orchestration frameworks * Strong knowledge of Vector Databases: * Milvus * Pinecone * Chroma * FAISS * Experience with retrieval architectures: * RAG * Hybrid retrieval * Graph-based retrieval * Hands-on experience fine-tuning and evaluating LLMs using: * LoRA * QLoRA * PEFT * Experience integrating AI capabilities into production applications and mission systems. * Strong understanding of AI deployment and production environments. Preferred Qualifications: * Familiarity with Agentic AI frameworks: * LangGraph * AutoGen * CrewAI * DSPy * Experience with multi-agent reasoning systems. * Understanding of: * Prompt Engineering * Retrieval Quality * Grounding Techniques Exposure to: * GPU-based inference environments * Edge AI deployments * Bachelor's or Master's degree in: * Computer Science * Engineering * Data Science * Related technical disciplines * Active Secret Clearance preferred. * Ability to obtain security clearance is required. Soft Skills: * Strong analytical and problem-solving skills. * Excellent written and verbal communication abilities. * Ability to collaborate effectively with cross-functional teams. * Strong documentation and knowledge-sharing practices. * Ability to work in mission-critical and highly secure environments. * Self-driven mindset with strong ownership and accountability. * Ability to thrive in fast-paced engineering environments. * Additional Notes * Opportunity to support Department of Defense (DoD) and Intelligence Community (IC) initiatives. * Focus on production-grade AI/ML systems and operational mission impact. * Exposure to cutting-edge technologies including: * LLMs * RAG Architectures * Vector Databases * Agentic AI * MLOps * Multi-Agent Systems * Engineers with security clearance backgrounds are highly preferred. * Ability to obtain an Active Secret Clearance is mandatory. Mandatory Skills: * Python * PyTorch * TensorFlow * Scikit-learn * Hugging Face * LangChain * MLOps * MLflow * Kubeflow * DVC * Vector Databases * Milvus * Pinecone * Chroma * FAISS * Retrieval-Augmented Generation (RAG) * LoRA * QLoRA * PEFT * Large Language Models (LLMs) * AI Model Fine-Tuning * Production AI Deployment * Agentic AI Frameworks * LangGraph * AutoGen * CrewAI * DSPy * Prompt Engineering * Multi-Agent Systems * DoD Environment Experience * Defense AI Security * AI Assurance * Secret Clearance Eligibility ## Description Frontier Technology Inc. (FTI) is seeking a highly skilled and hands-on AI/ML Engineer to design, develop, and deploy advanced machine learning solutions supporting Department of Defense (DoD) and Intelligence Community (IC) missions. This role is ideal for engineers who enjoy building end-to-end AI pipelines, developing production-grade systems, and delivering operational impact through modern AI technologies., * Design, develop, and deploy AI/ML models and pipelines to meet mission and performance objectives. * Build, train, fine-tune, and optimize machine learning models using PyTorch, TensorFlow, Scikit-learn, Hugging Face, and LangChain. * Develop and operationalize MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent orchestration frameworks. * Implement and optimize Vector Databases including: * Milvus * Pinecone * Chroma * FAISS * Develop retrieval architectures utilizing: * Retrieval-Augmented Generation (RAG) * Graph-based retrieval * Hybrid retrieval models * Write efficient Python code for: * Data ingestion * Feature engineering * Embeddings generation * Inference services * Fine-tune and optimize LLMs and task-specific models using: * LoRA * QLoRA * PEFT * Contribute to agent-based AI applications using: * LangGraph * AutoGen * CrewAI * DSPy * Integrate AI capabilities into production systems using APIs, event-driven workflows, and UI copilots. * Collaborate with data engineers, software developers, and mission analysts to ensure AI solutions are production-ready. * Participate in peer reviews, maintain shared repositories, and document experiments and models for reproducibility. ## Related Videos - [AI Killed DevOps... 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