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Hugging Face Jobs in Virginia (NOW HIRING)

REI Systems

Principal AI Engineer

Sterling, VA · On-site +1

Build, train, deploy and optimize machine learning models using PyTorch, Hugging Face, Scikit-learn, and LangChain/LangGraph. * Ensure AI/ML solutions meet performance, accuracy, security, privacy ...

REI Systems

Principal AI Engineer

Sterling, VA · On-site

Build, train, deploy and optimize machine learning models using PyTorch, Hugging Face, Scikit-learn, and LangChain/LangGraph. * Ensure AI/ML solutions meet performance, accuracy, security, privacy ...

Steampunk

AI Developer

Mclean, VA

$115K - $145K/yr

Strong proficiency in Python and modern AI frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, or similar. * Demonstrated ability to design and develop ...

ITC Federal, Inc.

Full Stack Developer - AI/ML

Fairfax, VA · On-site +1

$180K - $220K/yr

Experience with AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, OpenAI APIs) * Experience building data pipelines and working with big data technologies * Hands-on experience with cloud ...

Steampunk

AI Developer

Mclean, VA · On-site +1

$145K - $185K/yr

Deep expertise in modern AI frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, and relevant orchestration tools. * Proven experience building production-grade ...

Steampunk

Senior AI Developer

Mclean, VA · On-site

$140K - $190K/yr

Strong proficiency in Python and modern AI frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, or similar. * Demonstrated ability to design and develop ...

Steampunk

Senior AI Developer

Mclean, VA · On-site

$140K - $190K/yr

Strong proficiency in Python and modern AI frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, or similar. * Demonstrated ability to design and develop ...

Steampunk

AI Developer

Mclean, VA · On-site

$115K - $145K/yr

Strong proficiency in Python and modern AI frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, or similar. * Demonstrated ability to design and develop ...

Steampunk

Senior AI Developer

Mclean, VA · On-site

$140K - $180K/yr

Strong proficiency in Python and modern AI frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, or similar. * Demonstrated ability to design and develop ...

Steampunk

AI Developer

Mclean, VA

$145K - $185K/yr

Deep expertise in modern AI frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, and relevant orchestration tools. * Proven experience building production-grade ...

Steampunk

AI Developer / Product SME

Mclean, VA

$145K - $185K/yr

Deep expertise in modern AI frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, and relevant orchestration tools. * Proven experience building production-grade ...

Steampunk

Senior AI Developer

Mclean, VA

$140K - $190K/yr

Strong proficiency in Python and modern AI frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, or similar. * Demonstrated ability to design and develop ...

Steampunk

AI Developer / Product SME

Mclean, VA

$145K - $185K/yr

Deep expertise in modern AI frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, and relevant orchestration tools. * Proven experience building production-grade ...

Steampunk

AI Developer

Mclean, VA

$115K - $145K/yr

Strong proficiency in Python and modern AI frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, or similar. * Demonstrated ability to design and develop ...

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How much do hugging face jobs pay per hour?

As of Jun 26, 2026, the average hourly pay for hugging face in Virginia is $15.32, according to ZipRecruiter salary data. Most workers in this role earn between $12.88 and $18.12 per hour, depending on experience, location, and employer.

Which 3 jobs will survive AI?

Jobs that require complex human interaction, creativity, and critical thinking, such as healthcare professionals, software developers, and educators, are likely to persist despite AI advancements. These roles often involve emotional intelligence, nuanced decision-making, and specialized skills that are difficult for AI to replicate. Continuous learning and adaptability are essential for job security in an evolving AI landscape.

What job makes $10,000 a month without a degree?

High-paying roles that can earn $10,000 a month without a degree include skilled trades such as commercial diving, certain sales positions like real estate or software sales, and specialized tech roles like web development or cybersecurity, which often value skills and certifications over formal education. Success in these jobs typically requires experience, technical skills, or industry certifications, and they may involve self-employment or freelance work.

What jobs pay $2000 a day?

High-paying jobs that can pay around $2000 a day often include specialized roles such as senior software engineers, data scientists, management consultants, and certain freelance or contract positions in finance, law, or technology. These roles typically require advanced skills, extensive experience, and sometimes certifications, and may involve project-based or consulting work with flexible schedules.

What is the difference between Hugging Face vs Machine Learning Engineer?

AspectHugging FaceMachine Learning Engineer
Required CredentialsTypically requires knowledge of NLP, deep learning, and Python; certifications are optionalRequires degrees in CS or related fields; experience with ML frameworks; certifications beneficial
Work EnvironmentCollaborative, research-focused, often in tech companies or startupsDevelopment, deployment, and optimization of ML models in various industries
Employer & Industry UsageUsed by AI/ML companies, research labs, and open-source communitiesEmployed across tech, finance, healthcare, and other sectors implementing ML solutions

Hugging Face primarily focuses on NLP tools, libraries, and open-source models, serving as a platform for AI research and development. Machine Learning Engineers develop, implement, and optimize ML models across various domains. While Hugging Face offers resources and tools that ML Engineers use, the roles differ: Hugging Face is a platform, whereas Machine Learning Engineer is a job role involving hands-on model development and deployment.

How much does Hugging Face pay?

Salaries at Hugging Face vary depending on the role, experience, and location, but the company generally offers competitive compensation for AI and machine learning positions. Entry-level roles may start around $80,000 annually, while more experienced engineers and researchers can earn over $150,000 per year. Benefits often include flexible schedules, remote work options, and opportunities to work with cutting-edge NLP tools.
What are popular job titles related to Hugging Face jobs in Virginia? For Hugging Face jobs in Virginia, the most frequently searched job titles are:
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What cities in Virginia are hiring for Hugging Face jobs? Cities in Virginia with the most Hugging Face job openings:
Hugging Face jobs near you
Infographic showing various Hugging Face job openings in Virginia as of June 2026, with employment types broken down into 9% As Needed, 52% Full Time, 3% Temporary, 33% Contract, and 3% Nights. Highlights an 78% Physical, 3% Hybrid, and 19% Remote job distribution, with an average salary of $31,875 per year, or $15.3 per hour.
Principal AI Engineer

Principal AI Engineer

REI Systems

Sterling, VA • On-site, Remote

Other

Posted 6 days ago

Job description

Overview
REI Systems' mission is to deliver reliable, innovative technology solutions that advance Federal clients' missions and exceed their expectations. Our technologists and consultants are passionate about solving complex challenges that impact millions of lives. We take a Mindful Modernization® approach in delivering our services, including application modernization, grants management, case management systems, government data analytics, and advisory services. This approach, the REI Way, ensures mission impact by aligning our clients' strategic objectives with measurable outcomes through people, processes, and technology.
We offer the same commitment to our employees by providing professional development, meaningful projects, and flexibility to spend time with family and friends. We believe employees are at their best when fulfilled in both their professional careers and their personal lives. Learn more at www.REIsystems.com.
Employees voted REI Systems a Washington Post Top Workplace in 2015, 2016, 2018, 2020, 2021, 2022, 2023, 2024, and 2025!
Responsibilities
Position Overview:
REI is advancing Artificial Intelligence to modernize federal digital platforms, improve decision-making, and accelerate mission outcomes through intelligent automation, data-driven solutions, and AI-enabled enterprise architectures.
The Principal AI Engineer provides strategic and hands-on technical leadership to integrate AI across cloud modernization, enterprise platforms, and digital transformation initiatives. This role guides agencies in adopting secure, scalable, and responsible AI capabilities aligned with federal compliance and mission needs.
Operating in an AI-enabled modernization environment, this leader ensures AI solutions enhance operational efficiency, strengthen system interoperability, and deliver measurable mission impact across federal programs supporting both growth (innovation, solutioning, and client pursuit support) and delivery (end-to-end implementation and operationalization).
Key Responsibilities and Activities
Solution Design and Implementation
  • Architect and design scalable AI/ML solutions using cloud platforms such as AWS, Azure, and Google Cloud Vertex AI.
  • Collaborate with cross-functional teams to gather requirements, assess feasibility, and define technical specifications for AI projects.
  • Develop and implement AI-driven prototypes and PoCs to demonstrate the value of AI to clients, including GenAI/RAG and agentic workflow demonstrations where applicable.
  • Define target architectures for LLMOps/MLOps, including model lifecycle management, evaluation, deployment patterns, and security controls.

AI/ML Model Development
  • Apply core data science techniques, including data preprocessing, feature engineering, and model selection.
  • Build, train, deploy and optimize machine learning models using PyTorch, Hugging Face, Scikit-learn, and LangChain/LangGraph.
  • Ensure AI/ML solutions meet performance, accuracy, security, privacy, and interpretability standards.
  • Experience with generative AI models and methodologies is a strong plus, including prompt engineering, fine-tuning, embeddings, RAG, evaluation harnesses, and safety/guardrails.
  • Implement agentic AI patterns such as tool/function calling, planner-executor flows, structured output, human-in-the-loop, and multi-step reasoning workflows.

Data Preparation and Integration
  • Analyze and preprocess structured and unstructured data for AI model development.
  • Collaborate with data engineers to design and optimize data pipelines for AI workflows.
  • Address data quality, completeness, and bias issues to ensure robust AI outcomes.
  • Leverage platforms like Databricks and Snowflakes for data processing and AI solution integration.
  • Implement modern unstructured data pipelines including document ingestion, chunking, metadata enrichment, embedding generation, and vector search using vector databases/indexes, and Knowledge Graphs.

Cloud Integration and Deployment
  • Utilize cloud-native AI/ML services, including managed AI services, AutoML, and serverless architectures, plus managed GenAI services (e.g., AWS Bedrock, Azure AI Studio/Azure Machine Learning, Vertex AI).
  • Deploy AI models and solutions in cloud environments, ensuring scalability and performance optimization using containers/Kubernetes, CI/CD, and infrastructure-as-code.
  • Monitor and maintain deployed models, iterating as necessary based on feedback and performance metrics, including model/agent observability, drift detection, cost controls, and quality regression testing.
  • Implement efficient LLM serving and integration patterns (as needed) and API gateway/zero-trust approaches.

Collaboration and Stakeholder Engagement
  • Partner with internal account teams across all Business Units to support pre-sales and sales activities by presenting AI solutions to Federal clients, including client workshops, solutioning, whiteboarding, proposal support, and technical volume contributions.
  • Collaborate with clients and stakeholders to align AI solutions with business goals and regulatory requirements.
  • Provide technical leadership and mentorship to junior team members and account team members on AI/ML methodologies, GenAI/agentic AI patterns, and best practices.

Low-Code and Emerging Technologies
  • Understand and incorporate AI features of low-code platforms like Salesforce and Appian into AI/ML solutions where applicable, and similar enterprise platforms as needed.
  • Advise on integrating low-code and AI capabilities to enhance application development processes, solution efficiency and effectiveness.
  • Stay up-to date on advancements in AI technologies and solutions, including agent frameworks, evaluation approaches, and responsible AI governance.

Qualifications
  • 8+ years of total experience, with at least 4+ years in AI/ML solution design and implementation and demonstrated GenAI/LLM delivery (preferred).
  • Proven track record of working with cloud-based AI/ML platforms (AWS, Azure, GCP), including production deployments and operational support.

Technical Skills
  • Proficiency in Python and experience with ML frameworks such as PyTorch, Scikit-learn, Hugging Face, and LangChain/LangGraph.
  • Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques, including LLM/agent evaluation.
  • Experience with cloud AI/ML services such as AWS SageMaker, AWS Bedrock, Azure ML / Azure AI Studio, or Vertex AI.
  • Familiarity with big data platforms like Snowflake and Databricks.
  • Experience with RAG architectures, Knowledge Graphs, Vector Search, and agent orchestration/tooling (e.g., LangChain/LlamaIndex/Semantic Kernel or similar).
  • Experience with MLOps/LLMOps tooling (e.g., MLflow, model registries, CI/CD, monitoring/observability) is a strong plus.
  • Understanding of low-code platforms with AI capabilities, such as Salesforce and Appian, is a plus.

Soft Skills
  • Strong problem-solving abilities and critical thinking skills.
  • Excellent communication and interpersonal skills, with the ability to articulate technical concepts to non-technical audiences.
  • Adaptability and eagerness to stay updated with evolving AI/ML technologies.

Preferred Qualifications
  • AI/ML certifications (e.g., AWS Machine Learning Specialty, AWS Generative AI, Azure AI Engineer).
  • Experience working with Federal agencies or large-scale enterprises.
  • Familiarity with ethical AI principles and responsible AI practices, including governance, model risk considerations, and auditability.

Additional Requirements
  • Ability to obtain and maintain relevant security clearances.

Join us at REI Systems and be at the forefront of Federal AI innovation, contributing to impactful solutions that drive mission-critical outcomes.
Education: Bachelor's degree in Computer Science, Data Science, or a related field; Master's degree preferred.
Location: Hybrid - Sterling, VA HQ (with flexibility for remote work as per company policy).
EEO Statement: REI Systems is an Equal Opportunity Employer
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