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Hugging Face Jobs in Minnesota (NOW HIRING)

ADMINISTRATOR L3

Minneapolis, MN · On-site

$45K - $121K/yr

Strong experience with NLP and LLM frameworks (e.g., spaCy, Hugging Face, Azure OpenAI/OpenAI). Proven hands-on expertise in Python for text processing, rule extraction, and workflow automation.

Experience with specific AI/ML frameworks (TensorFlow, PyTorch, Hugging Face Transformers) * Knowledge of MLOps tools and practices for model deployment and monitoring * Experience in tax, trade, or ...

Experience with specific AI/ML frameworks (TensorFlow, PyTorch, Hugging Face Transformers) * Knowledge of MLOps tools and practices for model deployment and monitoring * Experience in tax, trade, or ...

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How much do hugging face jobs pay per hour?

As of May 31, 2026, the average hourly pay for hugging face in Minnesota is $15.14, according to ZipRecruiter salary data. Most workers in this role earn between $12.69 and $17.88 per hour, depending on experience, location, and employer.

What professions make 500,000 a year?

Professions that can earn $500,000 or more annually include senior roles such as CEOs, investment bankers, specialized surgeons, and successful entrepreneurs. High earnings often require extensive experience, advanced skills, and often involve leadership or highly specialized knowledge in their fields.

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 Minnesota? For Hugging Face jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Hugging Face jobs in Minnesota look for? The top searched job categories for Hugging Face jobs in Minnesota are:
Infographic showing various Hugging Face job openings in Minnesota as of May 2026, with employment types broken down into 1% As Needed, 68% Full Time, 28% Part Time, 2% Temporary, and 1% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $31,489 per year, or $15.1 per hour.
Senior AI Solution Architect

Senior AI Solution Architect

smart folks inc

Minneapolis, MN • On-site

Full-time

Posted 20 days ago


Job description

Job Title: Senior AI Solution Architect

Location: Minneapolis, MN

Duration: Full-time

15+ years in software engineering, AI/ML solutions, Cloud modernization with strong presentation and customer engagement skills.

Role Overview: As a Senior AI Solution consultant, you will lead the design and implementation of cutting-edge AI solutions across diverse domains. You will collaborate with cross-functional teams to architect scalable, secure, and high-performance AI systems leveraging advanced machine learning, deep learning, and generative AI technologies. Able to work closely with customer to engage and win large AI related business across multiple LOBs.

Key Responsibilities:

  • Customer engagement: Able to connect with customers to understand business need, drive proposal presentation and win the same for Wipro
  • Solution Architecture: Understand and drive high level solutioning for AI systems, including data preprocessing data pipelines, model training, deployment, and integration with enterprise applications.
  • Generative AI & LLMs: Architect high level of solutions using Large Language Models (LLMs), multi-modal AI, and Retrieval-Augmented Generation (RAG).
  • Performance Optimization: Optimize AI models for speed, scalability, and cost efficiency using frameworks like DeepSpeed, PyTorch Lightning, and Hugging Face Accelerate.
  • Agentic AI: Drive autonomous AI agents leveraging frameworks like AutoGen, LangGraph, and Declarative Copilots.
  • Collaboration: Work with hyperscalers (AWS, Azure, GCP, IBM) to scale solutions from POC to production.
  • Domain Expertise: Deliver AI solutions tailored for healthcare domain.  — This is key

Must have Skills:

  • Programming: Python (expert), OOP, Data Structures & Algorithms
  • Design Patterns and Software Architecture
  • Python Libraries: NumPy, SciPy, Pandas, Matplotlib
  • AI Frameworks: PyTorch (preferred), TensorFlow, Scikit-learn
  • ML/DL fundamentals
  • Microservices, Containers (Docker), basic Kubernetes
  • Tools: Jupyter Notebook, GitHub, GitHub Copilot, JIRA, CI/CD, DevOps
  • Strong problem-solving and debugging skills

Advanced AI Skills:

  • LLM/AI Model Training: DeepSpeed, PyTorch FSDP, Hugging Face PEFT, LoRA/QLoRA
  • Evaluation Metrics for LLMs
  • Distributed Training: Ray (Core, Data, Train, Tune) 
  • PyTorch Ecosystem: PyTorch Lightning, Hugging Face Transformers, Accelerate
  • Additional Frameworks: TensorFlow, Keras, XGBoost
  • Agentic AI Frameworks: AutoGen, LangGraph, Declarative Copilots

Specialties:

  • AI System Design
  • Nvidia CUDA/HPC, Intel OpenVINO/OneAPI 
  • AI Model Performance Optimization
  • Responsible AI

Cloud AI Platforms:

  • AWS Bedrock, GCP Vertex AI, Azure OpenAI, IBM Watsonx 

Top AI Models:

  • Llama, Gemini, GPT, Claude

Qualifications:

  • Bachelor’s/Master’s in Computer Science, AI/ML, or related field
  • Proven experience in architecting enterprise-scale AI solutions
  • Strong leadership and communication skills

Best Regards,

Srinivas

Sr. US IT Recruiter

Email: srinivas@smartfolksinc.com


Smart Folks logo

About Smart Folks

Sourced by ZipRecruiter

Smart Folks Inc. (SFI) is a global IT Staff Augmentation and Consulting Services that discovers handpicked smart talent and routes them to the right path. Smart Folks Inc. was founded in 2011 and is headquartered in McKinney, Texas. We have global operations with localized detail to meet the high caliber needs of our clients.

Industry

It services

Company size

11 - 50 Employees

Headquarters location

McKinney, TX, US

Year founded

2011

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