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Hugging Face Jobs in Illinois (NOW HIRING)

Raks Group

QA Engineer with Gen AI

Chicago, IL

Design and implement GenAI-powered applications using multiple LLMs (e.g., OpenAI, Anthropic, Cohere, Hugging Face). * Develop intelligent workflows, RAG pipelines, and prompt engineering strategies ...

Royal Cyber, Inc.

IT Services Sales

Naperville, IL · On-site

$90K/yr

... Hugging Face); awareness of MLOps patterns. A data science, statistics, or ML engineering background is welcome - provided the candidate has client-facing instincts.What we offer Base salary $70,000 ...

Tekcel8

Gen AI

Chicago, IL · On-site

... Hugging Face Transformers · TensorFlow or PyTorch · Knowledge Graphs · Neo4j · Redis · Kafka · MLflow · Databricks · FastAPI · Streamlit or Gradio · MCP (Model Context Protocol) · A2A ...

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How much do hugging face jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for hugging face in Illinois is $14.98, according to ZipRecruiter salary data. Most workers in this role earn between $12.60 and $17.69 per hour, depending on experience, location, and employer.

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 Illinois? For Hugging Face jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Hugging Face jobs in Illinois look for? The top searched job categories for Hugging Face jobs in Illinois are:
What cities in Illinois are hiring for Hugging Face jobs? Cities in Illinois with the most Hugging Face job openings:
Hugging Face jobs near you
Infographic showing various Hugging Face job openings in Illinois as of July 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $31,155 per year, or $15 per hour.

Python AI Engineer (Local to Chicago Only)

Solution Partners, Inc.

Chicago, IL • On-site

Other

Re-posted 17 days ago

Job description

We are only considering candidates based in Chicago. First interview will be on site in the Chicago office with a technical assessment. Please do not apply if this first phase is not possible.

We are looking for an AI Engineer to design, develop, and deploy an intelligent, multilingual chatbot that helps users track their parcels seamlessly. The chatbot will integrate with Snowflake for data retrieval, leverage APIs or web scraping to fetch tracking updates from external systems and run as a containerized solution on Azure. We are seeking to hire an engineer who is passionate about building scalable, AI-powered applications. You’ll work at the intersection of backend development and AI integration, leveraging modern tools like LLMs, MongoDB, Docker, and best coding practices. You’ll be responsible for writing clean, efficient, and maintainable code while working closely product teams to deploy intelligent systems. We need a proactive, self-motivated leader who thrives in a dynamic environment.

Key Responsibilities

  • Design, develop, and maintain an AI-powered chatbot capable of handling multi-lingual conversations.
  • Implement Retrieval-Augmented Generation (RAG) workflows to improve response accuracy and reduce unnecessary LLM calls
  • Integrate AI and LLM tools (e.g., OpenAI, LangChain, Hugging Face) into real-world applications
  • Integrate chatbot with Snowflake to fetch tracking data using tracking IDs.
  • Develop web scraping and API connectors to external parcel tracking systems
  • Deploy and manage chatbot services on Azure using Docker containers.
  • Implement vector databases (e.g., Pinecone, FAISS, Chroma) for efficient context management and response caching.
  • Ensure code quality through best practices: clean code, testing, and code reviews.

Must-Have Skills

  • Programming: Strong proficiency in Python and relevant libraries (e.g., LangChain, FastAPI, BeautifulSoup, Requests
  • AI Tools & Frameworks: Experience with OpenAI, Hugging Face, or similar AI APIs
  • RAG Implementation: Hands-on experience integrating LLMs with vector databases and retrieval pipelines
  • NLP: Strong understanding of prompt design, token usage, embeddings, and language model
  • Data Integration: Experience connecting with Snowflake or similar dataware houses.
  • Deployment: Knowledge of Docker and Azure container deployments.
  • Web Scraping & APIs: Experience building scrapers or integrating with third-party APIs
  • Version Control: Familiarity with Git and CI/CD pipelines
  • Strong communication skills — able to explain complex AI concepts in simple terms
  • Collaborative attitude and openness to feedback

Nice-to-Have Skills

  • Familiarity with LLM orchestration frameworks (LangChain, LlamaIndex)
  • Exposure to multi-lingual NLP models or translation APIs

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