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Hugging Face Jobs in Washington (NOW HIRING)

Capital One

Manager, Data Scientist

Mclean, VA · On-site

Leverage a broad stack of technologies - Python, SQL, AWS, LangChain, Hugging Face Transformers, VectorDBs, Pytorch/TensorFlow, and more - to reveal the insights hidden within large volumes of ...

JCD Staffing

Full Stack Developer

Washington, DC · On-site

Experience with Azure OpenAI, OpenAI API, Hugging Face, or other AI/LLM APIs * Experience with GitHub Actions, Azure DevOps, or similar CI/CD tools * Familiarity with TypeScript, Azure cloud services ...

Freddie Mac

Senior Software Engineer (Gen AI)

Mclean, VA · On-site

$124K - $163K/yr

... Hugging Face, or PyTorch. • Demonstrated experience building RAG systems, agentic workflows, and LLM-powered applications at scale. • Solid knowledge of vector databases, embedding models, and ...

Waypoint Human Capital

SWE2 w/ Cloud

Annapolis, MD · On-site

$55.25 - $73.75/hr

Exposure to AI/ML tools (TensorFlow, PyTorch, Hugging Face). * Experience with Golang development. * Experience with identity management platforms (e.g., Keycloak)

NetSage

AI Analytic Software Engineer-Senior

Annapolis, MD · On-site

$121K - $159K/yr

Proficiency with modern version control and model/code management using Git, GitLab, Hugging Face, Bailo, or similar tools. * Experience with the following tech stack: * PySpark * Jupyter Notebooks

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How much do hugging face jobs pay per hour?

As of Jul 17, 2026, the average hourly pay for hugging face in Washington is $17.51, according to ZipRecruiter salary data. Most workers in this role earn between $14.71 and $20.67 per hour, depending on experience, location, and employer.

Can you make money on Hugging Face?

Hugging Face is a platform that offers opportunities for data scientists, machine learning engineers, and developers to monetize their skills through jobs, freelance projects, or contributing to open-source models. Earning potential depends on the type of work, experience, and whether you are employed directly or working independently. Building a strong portfolio and expertise in NLP and AI tools can increase income opportunities on the platform.

Which 3 jobs will survive AI?

Jobs that require complex human interaction, creativity, and critical thinking, such as healthcare professionals, educators, and skilled tradespeople, are likely to persist despite AI advancements. These roles often involve emotional intelligence, nuanced judgment, and hands-on skills that are difficult for AI to replicate. Continuous learning and adaptability remain important for job security in an evolving technological landscape.

What are Hugging Face jobs?

Hugging Face jobs refer to employment opportunities at the company focused on developing and maintaining open-source machine learning tools, especially in natural language processing. Roles may include software engineering, research, data science, and product management, often requiring skills in Python, deep learning frameworks, and collaboration in a tech environment.

How much do Hugging Face engineers make?

Hugging Face engineers' salaries vary based on experience, role, and location, but generally range from $100,000 to $180,000 annually. Senior positions and specialized roles in machine learning or software engineering tend to offer higher compensation, often including stock options and benefits.

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.

What are popular job titles related to Hugging Face jobs in Washington? For Hugging Face jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Hugging Face jobs in Washington look for? The top searched job categories for Hugging Face jobs in Washington are:
What cities in Washington are hiring for Hugging Face jobs? Cities in Washington with the most Hugging Face job openings:
Hugging Face jobs near you
AI Developer/ AI Engineer (Python Development background)

AI Developer/ AI Engineer (Python Development background)

Sage IT Inc

Reston, VA • On-site

$52.25 - $72/hr

Full-time

Posted 7 days ago

New

Job description


We have a job opportunity of a Role AI Developer with Python development background with given job description on fulltime . Please forward updated profiles to pkanthri@sageitinc.net .
Job Title: AI Developer with Python

Location: Reston, VA(Onsite)

 

Job Description

We are seeking a highly skilled AI Developer with a strong Python development background to design, develop, and deploy AI/ML-based applications and solutions. The ideal candidate should have hands-on experience in Python programming, machine learning frameworks, API integrations, and cloud technologies, along with a passion for building scalable AI-driven systems.

Key Responsibilities:

  • Design, develop, and implement AI/ML solutions using Python.
  • Build and optimize machine learning and deep learning models.
  • Develop scalable backend services and APIs for AI applications.
  • Work with structured and unstructured data for model training and analysis.
  • Integrate AI models with enterprise applications and cloud platforms.
  • Collaborate with cross-functional teams including Data Engineers, DevOps, and Business stakeholders.
  • Perform data preprocessing, feature engineering, and model evaluation.
  • Monitor, troubleshoot, and improve model performance in production environments.
  • Implement automation workflows and AI-powered tools.
  • Maintain code quality, documentation, and best development practices.

Required Skills:

  • Strong experience in Python development.
  • Experience with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, or Hugging Face.
  • Knowledge of Generative AI, LLMs, NLP, or Computer Vision concepts.
  • Experience with REST APIs, FastAPI, Flask, or Django.
  • Hands-on experience with data processing libraries like Pandas, NumPy, and PySpark.
  • Familiarity with vector databases, embeddings, and RAG architecture is a plus.
  • Experience with cloud platforms such as AWS, Azure, or GCP.
  • Knowledge of Docker, Kubernetes, CI/CD pipelines, and Git.
  • Understanding of SQL/NoSQL databases.
  • Strong problem-solving and analytical skills.