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Nlp Team Lead Jobs (NOW HIRING)

NLP Engineer with Security Clearance

Herndon, VA · On-site

$117K - $141K/yr

NLP ENGINEER About the Team Here at BTI360, we've built a culture that's passionate about ... As an NLP Engineer at BTI360, you will: • Lead end-to-end knowledge graph and knowledgebase ...

... a team leadership or senior technical lead capacity. * Broad expertise across multiple modeling domains, such as predictive analytics, NLP, optimization, or AI platform evaluation. * Strong ...

Ensure the safety, training, and culture of your team. * Lead by example and ensure compliance with all policies and procedures. * Accountable for People, Operations, Sales, and Profits. * Assist at ...

Responsibilities : • Lead end-to-end knowledge graph and knowledge base development efforts from ... Founded in 2004, the company is headquartered in Ashburn, USA, with a team of 51-200 employees. The ...

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Nlp Team Lead information

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How much do nlp team lead jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for nlp team lead in the United States is $25.73, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $24.04 per hour, depending on experience, location, and employer.

What is the difference between Nlp Team Lead vs Data Scientist?

AspectNlp Team LeadData Scientist
Required CredentialsMaster's or PhD in Computer Science, NLP, or related fields; experience with NLP tools and frameworksMaster's or PhD in Data Science, Statistics, or related fields; strong programming and analytical skills
Work EnvironmentLeads NLP projects, manages teams, collaborates with engineering and product teamsAnalyzes data, builds models, interprets results across various domains
Employer & Industry UsageTech companies, AI startups, research institutions focusing on NLP applicationsBroad industry use including tech, finance, healthcare, and marketing

The Nlp Team Lead primarily manages NLP projects and teams, requiring leadership skills and NLP expertise. In contrast, a Data Scientist focuses on data analysis and modeling across various domains. While both roles require strong technical credentials, the Nlp Team Lead emphasizes team management and NLP-specific knowledge, whereas Data Scientists have a broader data analysis focus.

What are popular job titles related to Nlp Team Lead jobs?

For Nlp Team Lead jobs, the most frequently searched job titles are:

Infographic showing various Nlp Team Lead job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 77% Full Time, 19% Part Time, and 3% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $53,524 per year, or $25.7 per hour.

NLP Engineer with Security Clearance

Herndon, VA • On-site

BTI360 Inc
Software Development • 51 - 200 employees

$117K - $141K/yr

Other

Re-posted 23 days ago


Key responsibilities

  • Lead end-to-end development of knowledge graphs and knowledge bases, including designing pipelines to extract, normalize, link, and organize information into scalable graph systems.

  • Design and evaluate extraction and resolution workflows, assessing entity extraction, linking, relationship quality, and knowledge base accuracy using appropriate methodologies and metrics.

  • Translate business requirements into technical solutions, communicate findings to stakeholders, and collaborate across teams to align strategies and contribute to proposals.


Job description

NLP ENGINEER About the Team
Here at BTI360, 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. BTI360 previously has been voted 10 years in a row as a TOP Place to Work by the Washington Business Journal.  BTI360 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: As an NLP Engineer at BTI360, you will: • Lead end-to-end knowledge graph and knowledgebase 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.  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 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