Job DescriptionACTIVE SECURITY CLEARANCE AT THE TS/SCI POLYGRAPH LEVEL IS REQUIREDWe are seeking an
Applied AI / Machine Learning Engineer to modernize and innovate the end-to-end analytic lifecycle. In this role, you will design and deploy production AI-enabled workflows and automated data processing solutions, actively replacing legacy workflows with next-generation, AI-driven tradecraft. You will operate at the intersection of technical engineering and mission strategy, developing scalable machine learning and Generative AI systems while serving as a key translator between complex technical data and leadership. The ideal candidate pairs strong programming and data engineering fundamentals with practical experience in deep learning, Retrieval-Augmented Generation (RAG), and model fine-tuning.
The annual base salary range for this role is $230,000-$272,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
Required Skills- Core Development & Big Data Processing: Strong proficiency in Python and hands-on experience building distributed data processing and transformation pipelines using PySpark.
- Applied AI / Machine Learning Frameworks: Practical experience training, fine-tuning, and evaluating models using industry-standard ML/DL libraries such as PyTorch, TensorFlow, or Scikit-Learn.
- Generative AI Architecture & Tradecraft: Direct experience designing and deploying Retrieval-Augmented Generation (RAG) architectures, advanced prompt engineering strategies, or parameter-efficient fine-tuning techniques (e.g., LoRA / QLoRA).
- Analytic Lifecycle Modernization: Demonstrated track record of identifying legacy manual or rules-based processes and successfully replacing them with automated, AI-driven solutions.
- Technical Communication & Stakeholder Bridging: Proven ability to author clear technical documentation, architectural specifications, and white papers, as well as present complex findings across leadership forums and cross-functional teams.
Education:
Bachelor's Degree in Data Science, Computer Science, Computational Linguistics, Mathematics, or a related technical discipline, PLUS
13+ years of professional experience in data science, NLP, or software engineering OR
High School Diploma / GED, PLUS
17+ years of specialized technical experience in lieu of a degree.
Desired Skills- GenAI Application Frameworks: Hands-on experience developing with orchestration and embedding frameworks such as LangChain, LlamaIndex, and the Hugging Face Transformers/Diffusers ecosystem.
- Multi-Language & Query Proficiency: Working knowledge of additional data manipulation languages, specifically SQL, R, or Scala.
- Vector Databases & Semantic Retrieval: Experience deploying and optimizing vector databases (e.g., Chroma, Milvus, Qdrant, Pinecone, or pgvector) for enterprise semantic search and retrieval systems.
- Model Deployment & MLOps: Familiarity with MLOps practices, containerization (Docker, Kubernetes), and model serving tools (e.g., vLLM, Triton, TGI, or BentoML).
- Data Visualization & Dashboarding: Experience creating interactive visual interfaces or dashboards (e.g., Streamlit, Gradio, Dash) to showcase model outputs and prototype tools directly to end users.
