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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff AI/ML Engineer (Large Language Model) (TS/SCI) {S} - **Company:** ARKA Group - **Location:** Aurora, CO, United States - **Experience:** Experienced - **Salary:** $150,000.0 - $200,000.0 - **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), Nvidia CUDA, Linux, Python (Programming Language), Machine Learning, NumPy, Software Deployment, Software Engineering, Virtualization Technology, Reinforcement Learning, Rust (Programming Language), ReactJS, Large Language Models, Prompt Engineering, Gitlab, Git, Pandas, Containerization, Scikit Learn, Kubernetes, Information Technology, HuggingFace, Rancher, Bitbucket, Machine Learning Operations, Virtual Agents, Functional Programming, GPT, Software Version Control, Software Library, Docker, Golang - **Published:** August 10, 2026 - **Apply:** https://www.clearancejobs.com/jobs/8774965/staff-aiml-engineer-large-language-model-tssci-s ## About the Role * B.S. in machine learning, computer science, mathematics, or related fields * 8+ 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 + Steering Techniques (e.g Sparse auto encoders, representation tuning) + 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, pgvector) + Using LLM Frameworks (e.g. LangChain, DSPy, Microsoft Agent Framework) + 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. NumPy, Pandas, Polars, scikit-learn, etc.) * Experience contributing on a team using version control (e.g. git, GitLab, Bitbucket) * Active TS/SCI U.S. Government Security Clearance, * M.S. 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: + Large Language Models and experience identifying ways to incorporate them into new domains and applications + Applying Transformer-based architectures to domains in other areas outside of Natural Language Processing (NLP) such as computer vision + Natural Language Processing algorithms such as BERT + Reinforcement learning and familiarity with Gymnasium Gym, OpenEnv, TorchRL, 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 GenAI Ops techniques (e.g. LLM-as-a-judge) and frameworks (e.g. LangFuse, MLFlow, Arize Phoenix) + Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain + Experience with Linux + Experience with CUDA and Python libraries such as CuPy, Numba, CuSignal, CuDF, etc. + 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 in application deployment, virtualization, and containerization (e.g. Podman, Docker, Kubernetes, Rancher) * Experience shaping and writing proposals * Adjudicated Counter Intelligence or Full Scope Polygraph, This job operates in a professional office environment. While performing the duties of this job, the employee routinely is required to use hands to keyboard, communicate, listen to, and interpret instructions and remain stationary for extended periods of the time. This would require the ability to move around the campus and occasionally move/lift items weighing up to 25 lbs. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of the job. ## Description The Staff AI/ML Engineer (LLMs) will lead the development of Agentic AI capabilities and other LLM based capabilities for a multitude of mission management applications., 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 * Lead and mentor a multidisciplinary team delivering advanced AI/ML solutions * Apply LLMs to complex domain-specific problems and operational workflows * Adapt and fine-tune foundation models for specialized use cases * Design and implement retrieval-augmented generation (RAG) systems and semantic search architectures * Build production-grade LLM applications and agentic systems * Deploy scalable AI solutions across cloud, on-prem, and hybrid environments * Analyze large, multi-modal datasets to extract meaningful features and actionable insights * Translate emerging research into applied, mission-relevant capabilities * Communicate technical strategy, status, and risks to internal and external leadership ## Related Videos - [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) - [Vectorize all the things! 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) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Inside the Mind of an LLM](https://www.wearedevelopers.com/videos/1617-inside-the-mind-of-an-llm) - [How to implement convenient Python bindings to C++](https://www.wearedevelopers.com/videos/618-how-to-implement-convenient-python-bindings-to-c) ## 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) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path)