> Markdown version of [/jobs/ext/2017457-principal-ai-ml-engineer-large-language-model](https://www.wearedevelopers.com/jobs/ext/2017457-principal-ai-ml-engineer-large-language-model). 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). --- # Principal AI/ML Engineer (Large Language Model) - **Company:** Caci Inc - **Location:** Aurora, CO, United States - **Experience:** Experienced - **Salary:** $114,600.0 - $252,100.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Artificial Neural Networks, Computer Vision, C Sharp (Programming Language), C++ (Programming Language), Cloud Computing, Nvidia CUDA, Linux, Python (Programming Language), Machine Learning, NumPy, Object Detection, OpenCV, Performance Tuning, Tensorflow, Software Deployment, Software Engineering, Virtualization Technology, Reinforcement Learning, Rust (Programming Language), Pytorch, ReactJS, Large Language Models, Prompt Engineering, Generative AI, Keras, Pandas, Containerization, Scikit Learn, Kubernetes, Information Technology, HuggingFace, Rancher, Variational Autoencoders, Functional Programming, GPT, Software Library, Docker, Golang - **Published:** August 10, 2026 - **Apply:** https://www.clearancejobs.com/jobs/8835342/principal-aiml-engineer-large-language-model ## About the Role Required: * Active TS/SCI Clearance * BS in machine learning, computer science, mathematics, or related fields. * 10+ years of experience, preferably in software development or as a data scientist with 2+ years of building LLM applications using some of the following: + Fine-tuning foundational models o Steering Techniques (e.g Sparse auto encoders, representation tuning) o Building adapters to use foundational models (e.g. PEFT, llama factory) + Prompt engineering techniques / Inference time techniques (e.g. chain of thought, tree of thoughts, etc.) + Using Retrieval Augmented Generation techniques to populate and query vector databases (e.g. Weaviate, pinecone) + Using LLM Frameworks (e.g. LangChain, DSPy) + Using AI APIs ( e.g AWS Bedrock, OpenAI) + Using LLM deployment frameworks (eg llama.cpp, vllm, tgi) + Developing UIs with ReAct * Experience leading an interdisciplinary team of researchers and software developers and working with a program manager to define project scope and schedule to ensure we meet project milestones as defined by our customers * Experience with Python and data science / machine learning libraries (e.g. PyTorch, TensorFlow, Keras, OpenCV, NumPy, Pandas, Polars, scikit-learn, etc. Desired: * MS or PhD in machine learning, computer science, mathematics, or related fields. * Experience leading an interdisciplinary team of researchers and software developers * Experience with any of the following Computer Vision domains: + Large Language Models and experience identifying ways to incorporate them into new areas and applications + Applying Transformer-based architectures to domains in other areas outside of Natural Language Processing (NLP) such as computer vision + Object detection algorithms such as YOLO and Faster-RCNN + Natural Language Processing algorithms such as BERT + Generative Adversarial Networks and Variational Autoencoders + Reinforcement learning and familiarity with Gymnasium Gym, RLlib, and Stable Baselines + Applying clustering algorithms and/or deep neural networks to real life problems + Implementing tracking and pattern-of-life algorithms * Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain * Experience with Computer Vision libraries such as OpenCV, Nerfstudio, FiftyOne, etc. * Experience with Linux * Familiarity with using AWS cloud computing resources such as EC2, S3, Lambda, etc. * Experience with any of the following additional languages: Java, C++, Rust, Go, and/or C# * Experience implementing algorithms on the GPU in Python or C++ using CUDA and other CUDA libraries * Experience with implementing tracking and pattern-of-life algorithms * Experience in application deployment, virtualization, and containerization (e.g. Podman, Docker, Kubernetes, Rancher) * Experience working with various Remote Sensing datasets (e.g. EO/OPIR/SAR images, passive RF, etc.) * Experience shaping and writing proposals ## Description * Lead and mentor a multidisciplined team consisting of developers and researchers to implement machine learning algorithms to solve a broad set of challenges for our various customers * Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as tasking collections, identifying gaps in collection plans, analyzing patterns of life, and more. * Fine tune foundation models and building adaptors for new applications (llama factory, PEFT) * Apply retrieval augmented generation (RAG) techniques to data to populate and query vector databases (e.g. Weaviate) * Build custom applications with LLM frameworks such as LangChain, DSPy * Deploy LLM solutions across cloud-based and local resources using kubernetes (llama.ccp, vllm etc) * Analyze large multi-domain datasets such as images, text and/or graph data, to identify statistically relevant features to build models that provide analysts with actionable data * Review relevant publications to understand and apply cutting edge concepts to defense and commercial applications * Interface with both internal and external leadership to communicate technical status ## Related Videos - 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Using linear algebra and NumPy to make your Python code lightning fast.](https://www.wearedevelopers.com/videos/562-vectorize-all-the-things-using-linear-algebra-and-numpy-to-make-your-python-code-lightning-fast) - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) - [Speak, Code, Deploy: Transforming Developer Experience with Voice Commands](https://www.wearedevelopers.com/videos/1159-speak-code-deploy-transforming-developer-experience-with-voice-commands) - [Creating Industry ready solutions with LLM Models](https://www.wearedevelopers.com/videos/899-creating-industry-ready-solutions-with-llm-models) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [The Best Large Language Models on The Market](https://www.wearedevelopers.com/magazine/319-the-best-large-language-models-on-the-market) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)