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BTI360

Software development for federal big data

NLP Engineer

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeHerndon, VA, USA

About the Job

Requirements

  • Active Secret or higher security clearance, or the ability to obtain one.
  • At least 5 years of experience in data science or machine learning roles with demonstrated impact on production systems.
  • Deep expertise in natural language processing techniques.
  • Experience building knowledge graphs using Resource Description Framework or Labeled Property Graph models, including schema and ontology design.
  • Experience with knowledge graph construction pipelines, including rule- and large language model-based named entity recognition, relation extraction, entity normalization, and entity disambiguation or linking.
  • A proven track record of model evaluation using appropriate metrics and methodologies for different problem types, such as precision and recall, silhouette scores, and benchmarks.
  • Strong scripting skills and experience with artificial intelligence and machine learning frameworks, including scikit-learn, PyTorch or TensorFlow, transformers, and data manipulation libraries; proficiency with Jupyter notebooks for exploratory analysis and experimentation.
  • Basic software engineering practices, including Git, continuous integration and continuous delivery, code reviews, and documentation, and the ability to access and leverage remote application programming interfaces.
  • Comfort working in cloud platforms such as AWS, Azure, or GCP.
  • Excellent communication skills and experience translating technical metrics into business value and presenting findings to leadership and customers.
  • Ability to work independently.
  • Must maintain a primary residence within a two-hour drive of Herndon, Virginia to support onsite collaboration as needed.

Responsibilities

  • Lead end-to-end knowledge graph and knowledge base development from problem definition to production, designing pipelines that extract, normalize, link, and organize 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 knowledge base completeness and accuracy.
  • Translate business requirements into quantitative problems and communicate technical findings to 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 to 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 evaluating 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 modeling, extraction workflows, and knowledge base stewardship.

Desired Qualifications

  • Strong Python programming skills.
  • Experience with Graph RAG (Retrieval-Augmented Generation), including hybrid retrieval across graph traversal and dense or sparse vector search.
  • Experience with large or multimodal datasets.
  • Experience leading technical initiatives.

About the Company

BTI360

Software development for federal big data

BTI360 develops big data software solutions for federal government clients, focusing on distributed search, machine learning, and cloud engineering. Their products help mission users spend less time sifting through content and more time deriving insights, delivered through custom software that leverages scalable data processing and analytics. The company differentiates itself with a tight-knit, open culture that prioritizes investing in people—through code katas, targeted trainings, and conferences—and by empowering engineers to lead ideas. Its goal is to attract top engineers, invest in their growth, and enable them to create lasting, impactful solutions for public sector customers.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
Ashburn, VA
Founded
2004

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