Data Scientist SME AI/ML

Leidos•Odenton, MD

20h

About The Position

Leidos Cyber & Information Sciences Division of the Cyber & Analytics Business Area is seeking an AI & Analytic Systems SME to serve as a Technical Closer for our COSS 3.0 program. You will architect the frameworks that achieve analytic superiority and actively perform the engineering required to push AI capabilities into production. You are expected to mentor senior technologists by example—working "fingers-on-keyboard" to solve the command's most complex technical roadblocks. If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

Requirements

Expertise in deploying LangGraph, CrewAI, or AutoGPT.
Hands-on fine-tuning of open-source models (Llama 3, Mistral) in air-gapped enclaves using PyTorch or TensorFlow.
Direct engineering of Retrieval-Augmented Generation (RAG) stacks using LangChain and vector databases (Milvus or Pinecone).
Proficiency in unified mission systems (e.g., Kudu Dynamic, TACMS, Maven Support Systems) with custom API integration skills.
Mastery of Python, Go, and Bash.
12–15+ years in technical roles.
5+ years specifically in Machine Learning Engineering or Data Science.
3–5 years working within the IC/DoD (Intelligence Community/Dept. of Defense) ecosystem, specifically with systems like Maven or TACMS.
Master’s Degree or PhD in Data Science, Artificial Intelligence, Computer Science, or Mathematics.
TS/SCI with CI Poly required.

Nice To Haves

Google Professional ML Engineer, AWS Machine Learning Specialty, or NVIDIA Generative AI/LLM Associate.
Military Equivalency: CMF Work Role Certification (Exploitation/Network Analyst) or experience as a 170A/17A.
A Bachelor’s degree with an additional 5+ years (totaling 15-20) of high-level engineering experience can often substitute for a Master's, especially if backed by the "Military Equivalency" noted in the description.
Deep understanding of hardware constraints and model weights that usually comes from advanced academic or specialized research backgrounds.

Responsibilities

Deploying LangGraph, CrewAI, or AutoGPT to scale network defense at "wire speed."
Hands-on fine-tuning of open-source models (Llama 3, Mistral) in air-gapped enclaves using PyTorch or TensorFlow.
Direct engineering of Retrieval-Augmented Generation (RAG) stacks using LangChain and vector databases (Milvus or Pinecone).
Proficiency in unified mission systems (e.g., Kudu Dynamic, TACMS, Maven Support Systems) with custom API integration skills.
Mentoring senior technologists by example—working "fingers-on-keyboard" to solve the command's most complex technical roadblocks.