1

Senior Natural Language Processing Engineer Jobs in Virginia

Senior Labor Category: Minimum 8 years of experience with a Bachelor's degree; or 7 years of ... Advanced research experience in machine learning, deep learning, natural language processing ...

Agentic AI Engineer Required Skills * 3+ years of experience building production-level AI or ML ... with Natural Language Processing (NLP) * The AI models are being built ontop of the current ...

Agentic AI Engineer Required Skills * 3+ years of experience building production-level AI or ML ... with Natural Language Processing (NLP) * The AI models are being built ontop of the current ...

Showing results 41-60

Senior Natural Language Processing Engineer information

What does a senior natural language processing engineer do?

A Senior Natural Language Processing (NLP) Engineer designs and implements advanced algorithms that enable computers to understand, interpret, and generate human language. They work on tasks such as text classification, sentiment analysis, machine translation, and conversational AI. In addition to developing NLP models, they often lead projects, mentor junior team members, and collaborate with data scientists, software engineers, and product managers to build and deploy language-based applications. Their expertise helps organizations leverage language data to solve complex problems and improve user experiences.

What are the key skills and qualifications needed to thrive as a senior natural language processing engineer, and why are they important?

To thrive as a Senior Natural Language Processing Engineer, you need a deep understanding of machine learning, linguistics, and advanced programming skills in languages like Python, typically backed by a degree in computer science or a related field. Familiarity with NLP frameworks (such as spaCy, NLTK, or Hugging Face), cloud platforms, and experience with deep learning libraries like TensorFlow or PyTorch are crucial. Strong problem-solving abilities, effective communication, and the ability to work collaboratively in multidisciplinary teams are standout soft skills. These skills and qualities are essential for developing, deploying, and refining language-based AI solutions that meet complex business and user needs.

What are some common challenges faced by senior natural language processing engineers when deploying NLP models to production?

Senior NLP Engineers often encounter challenges such as ensuring model scalability, maintaining accuracy with real-world data, and addressing data privacy concerns. Deploying models at scale requires optimizing for speed and efficiency, as well as monitoring performance to handle domain shifts or unexpected inputs. Collaboration with DevOps and data engineering teams is crucial to integrate models seamlessly into existing pipelines and to ensure robust, maintainable solutions.

What is the difference between Senior Natural Language Processing Engineer vs Data Scientist?

AspectSenior Natural Language Processing EngineerData Scientist
Required CredentialsAdvanced degree in CS, NLP, or related field; experience with NLP frameworksDegree in CS, statistics, or related; data analysis skills
Work EnvironmentDevelops NLP models, algorithms, and language-specific toolsAnalyzes data, builds predictive models, visualizes insights
Employer & Industry UsageTech companies, AI startups, research institutions focusing on language techVarious industries including finance, healthcare, marketing

While both roles require strong analytical skills and programming knowledge, Senior NLP Engineers specialize in language-specific models and algorithms, whereas Data Scientists focus on broader data analysis and predictive modeling across various data types.

What are the most commonly searched types of Natural Language Processing Engineer jobs in Virginia?

The most popular types of Natural Language Processing Engineer jobs in Virginia are:

What job categories do people searching Senior Natural Language Processing Engineer jobs in Virginia look for?

The top searched job categories for Senior Natural Language Processing Engineer jobs in Virginia are:

What cities in Virginia are hiring for Senior Natural Language Processing Engineer jobs?

Cities in Virginia with the most Senior Natural Language Processing Engineer job openings:

Full-time

Re-posted 18 days ago


Job description

Closure Technologies is seeking a AI/ML Engineer who will Implement and maintain Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) into applications, supported by API development and optimizing data storage through Postgres schema refinement.

Clearance Requirement: TS/SCI with Polygraph

Key Responsibilities:

  • Implement and maintain RAG pipelines, including document processing, embedding generation, retrieval configuration, and prompt assembly.
  • Integrate LLMs into applications using available APIs and frameworks.
  • Develop and maintain REST API interactions to support data retrieval and system integration.
  • Design or refine Postgres schemas to improve data organization and query performance.

Required Qualifications:

  • Demonstrated ability to conduct independent technical research, evaluate emerging AI/ML approaches, and apply advanced analytical problem-solving comparable to PhD-level research environments.
  • Ability to rapidly learn and apply new AI/ML methodologies, tools, and frameworks in support of evolving mission requirements.
  • Experience developing AI/ML applications focused on Retrieval-Augmented Generation (RAG), semantic retrieval, LLM integration, or related AI workflows.
  • Strong proficiency in Python and modern AI/ML libraries, frameworks, and API integrations.
  • Active/current TS/SCI with required polygraph.
  • Willingness to work onsite full time.
  • US citizenship required.
  • Senior Labor Category: Minimum 8 years of experience with a Bachelor's degree; or 7 years of experience with a Masters degree; or 6 years of experience with a Doctorate

Preferred Qualifications:

  • Advanced research experience in machine learning, deep learning, natural language processing, generative AI, reinforcement learning, computer vision, or related disciplines.
  • Experience publishing research, contributing to open-source AI/ML initiatives, or leading experimental and prototype development efforts.
  • Familiarity with model evaluation frameworks, fine-tuning workflows, inference optimization, and AI observability/monitoring tools.
  • Experience with vector databases, AWS/cloud environments, Docker, and containerized AI/ML development workflows.
  • Experience designing and integrating REST APIs and scalable data architectures.