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Hugging Face Jobs in Michigan (NOW HIRING)

Software People, Inc.

AI Developer

Lansing, MI · On-site

Skills Needed • 3+years in TensorFlow, PyTorch, Keras, or Scikit-learn. • 3+ years in microservices. • 3+years in SpaCy, NLTK, or Hugging Face's • 3+years in Tesseract, Google Vision API, or ...

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How much do hugging face jobs pay per hour?

As of Jul 7, 2026, the average hourly pay for hugging face in Michigan is $13.47, according to ZipRecruiter salary data. Most workers in this role earn between $11.30 and $15.91 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 Michigan? For Hugging Face jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Hugging Face jobs in Michigan look for? The top searched job categories for Hugging Face jobs in Michigan are:
What cities in Michigan are hiring for Hugging Face jobs? Cities in Michigan with the most Hugging Face job openings:
Hugging Face jobs near you
Infographic showing various Hugging Face job openings in Michigan as of July 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $28,022 per year, or $13.5 per hour.
AI Developer

AI Developer

Software People, Inc.

Lansing, MI • On-site

Contractor

Re-posted 5 days ago

Job description

Phone/Skype Hire. Onsite from day 1 / Hybrid

Location: Lansing, MI

Duration: 12+ months

Responsibilities

The position is responsible for providing ongoing maintenance and support of GCP applications such as Document AI (DOC AI) for vital records within our department. The DOC AI is a Google Cloud product that is used to scan paper marriage licenses, extract index information and images to FileNet and stored in a on-prem application called VERA. The application is utilized by Vital Records employees. Changes are being made to enhance the stability and functionality of the systems.The resource is integral to developing and maintaining DOC AI solution, streamlining critical business processes, data integrity, SEM/SUITE compliance, and securing the applications.  The resource also performs as a technical lead and provides technical guidance to the other developers in the department.  As a technical lead, the resource participates in a variety of analytical assignments that provide for the enhancement, integration, maintenance, and implementation of projects.  The resource also provides technical oversight to developers in the team that support other critical applications . Not having a resource on staff will lead to MDHSS manually documenting and developing screen plans that can lead to errors causing data integrity issues and can eventually lead to incorrect information being processed and reporting of the patient information.

Skills Needed

•             3+years in TensorFlow, PyTorch, Keras, or Scikit-learn.

•             3+ years in microservices.

•             3+years in SpaCy, NLTK, or Hugging Face’s

•             3+years in Tesseract, Google Vision API, or AWS Textract.

•             3+years in Dialogflow ES or CX, Google Assistant SDK, or other Google Cloud chatbot development tools

•             3+years in RESTful APIs and webhooks

•             3+years in SQL, R, and/or Pandas.

•             3+ years in cloud computing and software development.

•             3+ years software development in Python, Java, JavaScript.

•             3+  years implementing core Artificial Intelligence (AI) and Machine Learning (ML) concepts.

•             3+ years designing, building, and managing Google Cloud Platform (GCP) solutions.

•             3+ years in projects development using  Angular/React JS, JavaScript framework.

•             3+ years programming in the JBOSS Enterprise SOA environment including JBOSS Workflow.

•             3+ years using CMM/CMMI Level 3 methods and practices.

•             3+ years implemented agile development processes including test driven development.

•             3+ years' Experience creating CI/CD pipelines using Azure DevOps.

•             Experience in programming languages such as Python, Java, JavaScript (Node.js), and/or C++.

•             Experience in Oracle/Data Bricks/Elastic/ELK.

•             Proficiency in data processing and analysis using tools such as SQL, R, and/or Pandas.

•             Experience in working with large datasets and data preprocessing techniques.

•             Proficiency in unit testing and integration testing for chatbot flows and APIs.

•             Familiarity with debugging tools and performance monitoring to ensure the chatbot runs smoothly.

•             Strong understanding of conversation design and user experience principles to create intuitive and engaging chatbot interfaces.

•             Ability to design, develop, and deploy AI and machine learning solutions.

•             Experience with machine learning algorithms and deep learning frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn.

•             Proficiency with Natural Language Processing (NLP) tools like SpaCy, NLTK, or Hugging Face’s Transformers for text-based document processing.

•             Knowledge of NLP concepts like intent recognition, entity extraction, and context management.

•             Strong understanding of neural networks, computer vision, natural language processing, and/or reinforcement learning.

•             Experience with OCR (Optical Character Recognition) Tesseract, Google Vision API, or AWS Textract.

•             Proficiency in Dialogflow ES or CX, Google Assistant SDK, or other Google Cloud chatbot development tools.

•             Experience in building, managing, and optimizing chatbot applications for different platforms (web, mobile, voice assistants).

•             Experience in working with RESTful APIs and webhooks to enable backend communication

•             Knowledge of cloud technologies such as AWS, Google Cloud AI, or Azure AI services for document processing and AI model deployment.

•             Experience with Google Cloud Platform (GCP), including Google Cloud Functions, App Engine, and Firestore for deploying chatbots.

•             Ability to design effective conversational flows, manage dialogue context, and improve user satisfaction.

•             Familiarity with agile development methodologies and version control systems like Git.

•             Strong problem-solving and analytical skills with a focus on continuous improvement."