Staff AI/ML Engineer (Large Language Model) (TS/SCI) {S} with Security Clearance

ARKA Group L.P. ("ARKA") is an advanced technologies company serving the U.S. military, intelligence community, and commercial space industry delivering next‑generation solutions to support the national security space enterprise. Built on more than six decades of excellence, ARKA brings modern approaches and a culture of innovation to the challenges of today. Join the ARKA team to learn how Beyond Begins Here. Discover your next career opportunity now! Position Overview 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. We offer generous relocation benefits for eligible candidates. In support of work/life balance, many positions are available for a flexible schedule within the pay period. Ask us about the opportunity for flex scheduling if that’s of interest to you. Responsibilities 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 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. Develop 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 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 to a team using version control (e.g., git, GitLab, Bitbucket). Required Qualifications 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. 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). 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 (e.g., llama.cpp, vllm, TGI). Active TS/SCI U.S. Government Security Clearance. Preferred Qualifications M.S. or Ph.D. in machine learning, computer science, mathematics, or related fields. Experience leading an interdisciplinary team of researchers and software developers. 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, 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). #J-18808-Ljbffr NLP PEOPLE