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Language Model Jobs in Ashburn, VA (NOW HIRING)

Node.Digital

Senior Data Engineer

Washington, DC · On-site +1

$120K - $163K/yr

Demonstrated familiarity with AI coding assistants and large language model integration patterns. * PySpark or Polars at production scale. * Entity resolution and attribute normalization across ...

Booz Allen Hamilton

Agentic Solutions Engineer

Mclean, VA · On-site

$69.40 - $158/hr

Integrate large language model capabilities into applied workflows, moving beyond experimentation to build AI features that solve real workforce challenges. Responsibilities * Design, develop, test ...

Argo Cyber Systems

AI/ML Automation Engineer

Arlington, VA · On-site

$120K - $135K/yr

Experience integrating Large Language Models (LLMs) * Experience with Amazon Bedrock and AWS AI services * Experience building REST APIs and cloud-native applications * Experience with Git, CI/CD ...

Argo Cyber Systems

AI/ML Automation Engineer

Arlington, VA · On-site

$120K - $135K/yr

You will collaborate with cyber analysts, data scientists, software engineers, cloud architects, and mission stakeholders to implement advanced machine learning models, Large Language Model (LLM ...

VTG

AI Architect with Security Clearance

Chantilly, VA · On-site

Large Language Model (LLM) integrations * Autonomous and semi-autonomous workflows * AI orchestration frameworks * Predictive analytics and traditional ML models Lead the end-to-end AI lifecycle ...

VTG

AI Architect

Chantilly, VA · On-site

Large Language Model (LLM) integrations * Autonomous and semi-autonomous workflows * AI orchestration frameworks * Predictive analytics and traditional ML models Lead the end-to-end AI lifecycle ...

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All JobsLanguage Model JobsLanguage Model Jobs in Ashburn, VA

Language Model information

See Ashburn, VA salary details

$10

$32

$68

How much do language model jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for language model in Ashburn, VA is $32.08, according to ZipRecruiter salary data. Most workers in this role earn between $19.42 and $40.05 per hour, depending on experience, location, and employer.

What is a language model?

Language models are artificial intelligence systems designed to understand, generate, and manipulate human language. They are trained on vast amounts of text data to predict the next word in a sequence, answer questions, write content, translate languages, and perform other language-related tasks. Modern language models, such as those based on deep learning, have revolutionized natural language processing by enabling more accurate and context-aware interactions between humans and machines.

What are the common challenges faced by professionals working on language model development teams?

Professionals developing language models often encounter challenges such as managing large datasets, addressing biases in training data, and optimizing model performance while balancing computational resources. Collaboration with cross-functional teams—including data scientists, engineers, and domain experts—is essential to ensure the model's accuracy and relevance. Additionally, staying current with rapid advancements in AI research and maintaining responsible AI practices are crucial aspects of the role.

What are the key skills and qualifications needed to thrive as a language model, and why are they important?

To thrive as a Language Model Engineer, you need a strong background in computer science, machine learning, and natural language processing, often supported by a relevant degree. Experience with frameworks like TensorFlow or PyTorch, and familiarity with large-scale data processing tools, are typically required. Strong analytical thinking, collaboration, and problem-solving skills help in designing effective models and working with cross-functional teams. These capabilities are crucial for developing performant and accurate language models that meet complex real-world communication needs.

What is the difference between Language Model vs Data Scientist?

AspectLanguage ModelData Scientist
Required CredentialsNone specific; knowledge of NLP and AI concepts helpfulBachelor's or higher in Data Science, Statistics, or related fields
Work EnvironmentAI development teams, research labs, tech companiesBusiness, finance, healthcare, and various industries
Employer & Industry UsageUsed in AI applications, chatbots, content generationAnalyzing data, building models, providing insights

While both roles involve working with data and AI, a Language Model is an AI system designed to understand and generate human language, often developed by AI engineers. A Data Scientist analyzes data to extract insights and build predictive models, often utilizing language models as tools. Understanding the differences helps clarify career paths and job expectations in the AI and data fields.

What are popular job titles related to Language Model jobs in Ashburn, VA?

For Language Model jobs in Ashburn, VA, the most frequently searched job titles are:

What job categories do people searching Language Model jobs in Ashburn, VA look for?

The top searched job categories for Language Model jobs in Ashburn, VA are:

Language Model jobs near you

Senior Data Engineer

Node.Digital

Washington, DC • On-site, Remote

$120K - $163K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 8 days ago

Job description

Senior Data Engineer
Location: Herndon, VA (Remote Work)
Must have an Public Trust Clearance
KEY RESPONSIBILITIES
• Provide authoritative expertise on data engineering methods and best practices, including code first development approaches and modern pipeline design patterns.
• Design, implement, and maintain the data architecture that supports products and end users, with all assets managed under source control.
• Design, implement, and maintain ELT and ETL pipelines for efficient processing of source data in Azure Synapse and Azure Machine Learning, using both SDK V1 and SDK V2.
• Migrate source data identified by SBA OIG into Azure Data Lake Storage.
• Normalize entity attributes such as addresses, phone numbers, and other common fields.
• Review, maintain, and improve existing architecture and pipelines, including periodic audits addressing bottlenecks, deprecated dependencies, and architecture drift.
• Establish quality controls across all pipelines and introduce error handling, logging mechanisms, and validation checks.
• Incorporate source control across all pipelines and analytics codebases so code can evolve iteratively without destabilizing the architecture.
• Optimize ingestion, processing, and storage across a wide variety of datasets and data types, including modern columnar formats such as Parquet.
• Develop self service capabilities that let SBA OIG analysts query and export data for investigations and audits.
• Author robust standard operating procedures governing the authoring, development, validation, publishing, execution, and monitoring of all data pipelines and assets in the Azure environment.
• Produce detailed documentation of the data architecture, including data dictionaries, entity relationship diagrams, and pipeline process maps.
• Maintain and expand the environment with additional datasets and services on request, following a defined intake and testing process before production deployment.
• Stay current with emerging AI tooling relevant to data engineering and contribute to exploratory work evaluating automation and language model assisted capabilities.
Requirements
Education
Bachelor's degree in data engineering, computer science, data science, machine learning, mathematics, or a related field. Alternatively, five years of applied work experience in any of the same fields.
  • 5 years - Maintaining SQL databases and conducting advanced operations in SQL and T-SQL.
  • 5 years - Designing, implementing, and maintaining ELT and ETL processes in cloud based data analytics environments.
  • 3 years - Working in Azure Synapse and Azure Machine Learning with the modern data stack. Certifications preferred, DP-203 or equivalent.
  • 3 years -Manipulating data in Python. Pandas is required. PySpark and Polars preferred. Experience developing reusable, modular code preferred.

PREFERRED QUALIFICATIONS
  • DP-203, Microsoft Certified Azure Data Engineer Associate, or an equivalent current certification.
  • Implementing pipelines and infrastructure using code first approaches: Python SDK, CLI, REST APIs, or infrastructure as code tooling such as Terraform or Bicep.
  • Implementing source control and continuous integration and delivery workflows for data assets.
  • Demonstrated familiarity with AI coding assistants and large language model integration patterns.
  • PySpark or Polars at production scale.
  • Entity resolution and attribute normalization across records with inconsistent addresses, names, and identifiers.
  • Building self service analytic access for non engineering users.

Benefits
We are proud to offer competitive compensation and benefits packages to include
  • Medical
  • Dental
  • Vision
  • Basic Life
  • Health Saving Account
  • 401K matching
  • Three weeks of PTO/Sick
  • 11 Paid Holidays
  • Pre-Approved Online Training

Apply