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NLP Engineer - Clearance Required

Job in Herndon, Fairfax County, Virginia, 22070, USA
Listing for: BTI360
Full Time position
Listed on 2026-07-02
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 125900 - 247900 USD Yearly USD 125900.00 247900.00 YEAR
Job Description & How to Apply Below

About The Team

Here at BTI
360, we’ve built a culture that’s passionate about developing software engineers. Software doesn't build itself. People do. In fact, teams of people do. That's why our primary focus is on developing better craftsmen, better teammates, and better technical leaders. By putting people first, we're not just giving our teammates more opportunities to grow, we're also raising the bar of the software we ship.

BTI
360 has been voted 10 years in a row as a TOP Place to Work by the Washington Business Journal.

About the Role

BTI
360 is seeking an NLP Engineer who is passionate about transforming raw data into meaningful insights that drive strategic decision-making. In this role, you’ll work closely with our engineers and mission teams to tackle complex business problems using emerging AI technologies—specifically by extracting and linking critical entities to build and curate scalable graph databases and knowledge bases. You’ll thrive here if you are naturally curious, driven to ask the right questions, and energized by turning complexity into clarity.

Our NLP Engineers don’t just build models, they influence decisions; they map critical relationships, shape strategy, and help our customers navigate high‑impact mission challenges.

What You Will Do In This Role
  • Lead end-to-end knowledge graph and knowledge base development efforts from problem definition to production, designing pipelines that extract, normalise, link, and organise information into scalable graph-based systems.
  • Design and evaluate extraction and resolution workflows using sound methodologies and fit-for-purpose metrics to assess entity extraction, linking, relationship quality, and overall knowledgebase completeness and accuracy.
  • Translate business requirements into quantitative problems and communicate technical findings to both technical and non-technical stakeholders through reports, presentations, and direct customer engagement.
  • Drive technical decision-making for schema design, ontology alignment, extraction approaches, and graph architecture based on mission needs, data quality, and long-term maintainability.
  • Stay current with advances in knowledge representation and information extraction and introduce practical techniques, tools, and frameworks that improve graph construction, curation, and analytic value.
  • Apply analytical and statistical methods to validate extracted insights, measure data quality, and support confident decision-making from structured and unstructured sources.
  • Develop reports and whitepapers that evaluate solution alternatives based on impact, cost, technical feasibility, and alignment with strategic goals.
  • Collaborate across teams to align on strategy, provide data science expertise, and contribute to proposals and strategic initiatives.
  • Mentor junior data scientists by providing technical guidance, defining project direction, and sharing best practices in graph-oriented data modelling, extraction workflows, and knowledgebase stewardship.
Required Skills
  • Active Security Clearance (Secret or higher) or the ability to obtain one.
  • 5+ years of experience in data science or machine learning roles with demonstrated impact on production systems.
  • Deep expertise in natural language processing (NLP) techniques.
  • Experience building Knowledge Graphs using RDF or Labeled Property Graph (LPG) models, including schema/ontology design.
  • Experience with Knowledge Graph construction pipelines: rule- and LLM-based NER, RE, Entity Normalisation and Disambiguation/Linking.
  • Proven track record of model evaluation using appropriate metrics and methodologies for different problem types (precision/recall, silhouette scores, benchmarks, etc.).
  • Strong scripting skills with experience in AI/ML frameworks (scikit-learn, PyTorch/Tensor Flow, transformers) and data manipulation libraries, including proficiency with Jupyter notebooks for exploratory analysis and experimentation.
  • Basic software engineering practices such as git, CI/CD, code reviews, documentation, and ability to access and leverage remote APIs.
  • Comfortable working in cloud platforms (AWS, Azure, GCP).
  • Excellent communication skills with experience translating technical…
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