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Hugging Face Jobs in Arizona (NOW HIRING)

AI Engineer

Phoenix, AZ ยท On-site

... Hugging Face. Practical knowledge of model orchestration frameworks (e.g., LangChain, LlamaIndex, CrewAI), Familiarity with vector databases Experience with cloud platforms (AWS, Azure AI, Google ...

Flask, FastAPI, Hugging Face, Triton Inference Server * pgVector, Milvus, Prometheus, Elasticsearch, Kibana * CI/CD: Jenkins, GitLab CI, XL Release Location & Work Model Phoenix, AZ - Hybrid (3 days ...

Familiarity with machine learning frameworks and libraries like TensorFlow, PyTorch, or Hugging Face. * Strong analytical and problem-solving skills with a keen eye for detail. * Excellent ...

AI Engineer II

Phoenix, AZ ยท On-site

$125 - $150/hr

Generative AI platforms and frameworks such as OpenAI, Anthropic, LangChain, LlamaIndex, Hugging Face, or similar technologies. * Prompt engineering, evaluation methodologies, and retrieval-augmented ...

Lead AI Engineer

Phoenix, AZ ยท On-site

$99K - $131K/yr

Model-level work using PyTorch and the Hugging Face ecosystem (embeddings, fine-tuning, inference tooling), with some exposure to TensorFlow * Strong schema, validation, and state management ...

AI Engineer II

Phoenix, AZ

$88K - $121K/yr

Generative AI platforms and frameworks such as OpenAI, Anthropic, LangChain, LlamaIndex, Hugging Face, or similar technologies. * Prompt engineering, evaluation methodologies, and retrieval-augmented ...

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Hugging Face information

See Arizona salary details

$8

$14

$19

How much do hugging face jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for hugging face in Arizona is $14.40, according to ZipRecruiter salary data. Most workers in this role earn between $12.12 and $17.02 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 Arizona?

For Hugging Face jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Hugging Face jobs in Arizona look for?

The top searched job categories for Hugging Face jobs in Arizona are:

What cities in Arizona are hiring for Hugging Face jobs?

Cities in Arizona with the most Hugging Face job openings:

Infographic showing various Hugging Face job openings in Arizona as of August 2026, with employment types broken down into 82% Full Time, 16% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $29,961 per year, or $14.4 per hour.

AI Engineer

Phoenix, AZ โ€ข On-site

Contractor

Posted 13 days ago


Job description

AI Engineer - Agentic AI, Node Js
Typescript and Python, Gen AI, Agentic AI . Client is not considering candidates who do not have experience on this.
Technical Skills:
6+ years of experience building large-scale distributed systems + strong experience with LLM systems, agentic workflows or advanced ML infrastructure, async processing, queues, and streaming systems
Experience working on Typescript and Python, Gen AI, Agentic AI
Advanced proficiency in Python, Hands-on experience with PyTorch, TensorFlow, Hugging Face.
Practical knowledge of model orchestration frameworks (e.g., LangChain, LlamaIndex, CrewAI), Familiarity with vector databases
Experience with cloud platforms (AWS, Azure AI, Google Cloud Vertex AI) and containerization technologies
Proven ownership of complex, cross-cutting agentic systems spanning multiple teams or products.
Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud infrastructure.
Deep experience across the agentic AI stack, including planning, tool use, memory, and evaluation.
Fluency with AI-assisted and agentic development workflows.
Ability to influence technical direction and align teams without formal authority.
Problem-solving, cross-functional collaboration, and the ability to articulate complex AI concepts to non-technical business stakeholders