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Huggingface Jobs in Washington (NOW HIRING)

Proficiency with LangChain, HuggingFace, Transformers, OpenAI/Ollama APIs. * Experience to agentic AI frameworks like LangGraph, AutoGen, CrewAI. * Build and enhance GenAI-powered QE solutions, AI ...

Demonstrated professional or academic experience with the HuggingFace Transformers library and hub. * Demonstrated experience creating machine learning models that conduct text classification and ...

Demonstrated professional or academic experience with the HuggingFace Transformers library and hub. * Demonstrated experience creating machine learning models that conduct text classification and ...

Demonstrates professional or academic experience with the HuggingFace Transformers library and hub. * Demonstrates experience creating machine learning models that conduct text classification and ...

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How much do huggingface jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for huggingface in Washington is $28.28, according to ZipRecruiter salary data. Most workers in this role earn between $16.26 and $33.04 per hour, depending on experience, location, and employer.

What is a Huggingface job?

A Hugging Face job typically refers to a role at Hugging Face, a company specializing in machine learning and natural language processing (NLP). Employees at Hugging Face work on developing and maintaining open-source AI tools, including the popular Transformers library. Roles range from research and engineering to product and community development, often focusing on advancing state-of-the-art AI models.

What does a typical day look like for an engineer working at Hugging Face?

As an engineer at Hugging Face, your day typically involves collaborating with team members to design, develop, and improve state-of-the-art machine learning models and tools, with a strong focus on open-source NLP projects. You’ll participate in code reviews, experiment with new technologies, engage with the community through forums or GitHub, and help support user questions or issues. Expect a fast-paced, collaborative environment where cross-functional teamwork with product managers, researchers, and other engineers is common. The work is project-driven, with plenty of opportunities to contribute ideas, learn from experts, and advance your technical skills.

What are the key skills and qualifications needed to thrive in the Huggingface position, and why are they important?

To thrive in a role at Hugging Face, you typically need strong skills in machine learning, natural language processing (NLP), and software development, supported by a relevant degree in computer science or a related field. Familiarity with frameworks like PyTorch or TensorFlow, plus experience using version control systems such as Git, are often required; open-source contributions and cloud platform knowledge are a plus. Excellent communication, collaborative teamwork, and problem-solving abilities help candidates stand out in this dynamic, innovation-driven environment. These strengths are crucial because they enable individuals to develop high-impact AI tools, work effectively in interdisciplinary teams, and contribute to open-source communities.

What are the most commonly searched types of Huggingface jobs in Washington?

The most popular types of Huggingface jobs in Washington are:

What are popular job titles related to Huggingface jobs in Washington?

For Huggingface jobs in Washington, the most frequently searched job titles are:

What cities in Washington are hiring for Huggingface jobs?

Cities in Washington with the most Huggingface job openings:

Infographic showing various Huggingface job openings in Washington as of August 2026, with employment types broken down into 97% Full Time, and 3% Part Time. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $58,827 per year, or $28.3 per hour.

Data Scientist with Security Clearance

Fairfax, VA • On-site

Convirgence
IT Services • 11 - 50 employees

Other

Re-posted 8 days ago


Job description

Data Scientist McLean, VA SV-DS-MCL-001 Python NLP packages (Spacy, Gensim, NLTK); deep learning frameworks (PyTorch, Tensorflow, Keras); HuggingFace Transformers; SQL; Java Spring / Spring Data JPA; OOP, multithreading, JVM memory mgmt; Oracle; AWS; Linux; GPU accelerated computing