What you will do in this role:

As an NLP Engineer at BTI360, you will:

• Lead end-to-end knowledge graph and knowledge base development efforts 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 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 modeling, extraction workflows, and knowledgebase stewardship.

Qualifications Required:

• 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 Resource Description Framework (RDF) or Labeled Property Graph (LPG) models, including schema/ontology design
• Experience with Knowledge Graph construction pipelines: rule- and LLM-based Named Entity Recognition (NER), Relation Extraction (RE), Entity Normalization 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/TensorFlow, 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 metrics into business value and presenting findings to leadership and customers
• Ability to work independently
• Candidates must maintain a primary residence within a two‑hour drive of Herndon, VA to support onsite collaboration as needed.

Desired Skills:

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

The base salary pay range for this role is $125,900 - $247,900. This range reflects base compensation only and does not include benefits, bonuses, or additional pay incentives associated with the opportunity.