1

Hugging Face Jobs in Arizona (NOW HIRING)

AI Engineer II

Phoenix, AZ · On-site

$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 ...

Senior AI Model Fine-Tuning Engineer

Phoenix, AZ · On-site

$128K - $176K/yr

Experience with popular transformer architectures and frameworks like Hugging Face, TensorFlow, or PyTorch. * Deep understanding of LLM behaviors, including instruction-following, task completion ...

Senior AI Model Fine-Tuning Engineer

Phoenix, AZ · On-site

$128K - $176K/yr

Experience with popular transformer architectures and frameworks like Hugging Face, TensorFlow, or PyTorch. * Deep understanding of LLM behaviors, including instruction-following, task completion ...

Showing results 21-28

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 II

Phoenix, AZ • On-site

$88K - $121K/yr

Full-time

Posted 12 days ago


Job description

POSITION SUMMARY

McCarthy is seeking a full-time AI Engineer II who will be part of the Engineering and Intelligence team. In this role, you will design, build, and support AI-powered applications and workflows that help drive business value across the enterprise.

Working closely with the AI Manager, business stakeholders, and fellow engineers, you will contribute to the development of production-grade AI solutions, including generative AI, agentic workflows, advanced analytics, and enterprise integrations. This is a hands-on engineering role focused on implementation, experimentation, deployment, and continuous improvement of AI capabilities.

The ideal candidate combines strong software engineering fundamentals with experience in AI and data-driven applications. Experience working within Palantir Foundry, including ontology-driven development, data products, operational workflows, and AI-enabled solutions, is strongly preferred.

RESPONSIBILITES

  • Design, develop, test, and maintain AI-powered applications, services, and workflows that support enterprise business processes.
  • Build and support generative AI and agentic solutions using modern AI engineering practices and frameworks.
  • Develop and maintain data pipelines, integrations, and reusable data products that enable AI and analytics use cases.
  • Contribute to the design and evolution of data models and ontologies that support operational and analytical workflows.
  • Develop and optimize prompts, retrieval strategies, and agent workflows to improve solution effectiveness, reliability, and user experience.
  • Leverage AI-assisted development tools and coding copilots to accelerate delivery while maintaining high standards for code quality, testing, security, and maintainability.
  • Participate in MLOps and PromptOps processes, including deployment, monitoring, evaluation, versioning, and continuous improvement of AI systems.
  • Collaborate with business and technical stakeholders to translate business requirements into practical technical solutions.
  • Support production AI solutions through troubleshooting, performance tuning, monitoring, and ongoing enhancement activities.
  • Contribute to documentation, reusable patterns, and engineering best practices that improve team effectiveness and solution consistency.
  • Follow established AI governance, security, and Responsible AI standards throughout the solution lifecycle.

    QUALIFICATIONS

    • Minimum 3 years of experience in software engineering, AI engineering, machine learning, data engineering, or a related technical discipline.
    • Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or a related field (or equivalent practical experience).
    • Experience building and deploying AI-enabled applications or machine learning solutions in production environments.
    • Strong programming skills in Python and experience with modern software engineering practices.
    • Data pipelines, ETL/ELT processes, and API-based integrations
    • SQL and relational data modeling
    • Cloud platforms such as Azure, AWS, or GCP
    • Containerized and serverless application deployment patterns
    • Building solutions on enterprise AI and data platforms such as Palantir Foundry, Azure AI, AWS, GCP, or Dataiku.
    • Generative AI platforms and frameworks such as OpenAI, Anthropic, LangChain, LlamaIndex, Hugging Face, or similar technologies.
    • Prompt engineering, evaluation methodologies, and retrieval-augmented generation (RAG) patterns.
    • Experience with Palantir Foundry is strongly preferred, including familiarity with:
      • Ontology-driven application development
      • AIP and AI-enabled workflows
      • Data products and pipeline development
      • Workshop applications and operational workflows
      • Code Repositories and software delivery within Foundry environments
      • Understanding of responsible AI concepts, including transparency, human oversight, security, and governance practices.

      CHARACTERISTICS

      • Strong problem-solving and analytical skills with the ability to work through ambiguity and deliver practical solutions.
      • Effective communication skills and the ability to collaborate with technical and non-technical stakeholders.
      • Curiosity and enthusiasm for emerging AI technologies and software engineering practices.
      • Strong attention to quality, maintainability, and user experience.
      • Ability to learn new technologies quickly and apply them effectively in a business environment.
      • High degree of accountability, ownership, and commitment to delivering results.


      McCarthy is proud to be an equal opportunity employer, including disability and protected veteran status.
      NOTICE TO EXTERNAL SEARCH FIRMS: McCarthy’s Talent Acquisition Team is the only authorized representative permitted to engage with external search firms, staffing agencies, or other third-party recruiting partners. McCarthy maintains an Approved Agency List for recruiting partners, which is reviewed and updated annually.
      McCarthy will only consider submissions from agencies with a signed fee agreement in place for the current year. McCarthy does not accept unsolicited resumes, candidate submissions, or referrals from agencies that do not meet these requirements.
      If a candidate is submitted without an active agreement, McCarthy will have no obligation to pay any fees and reserves the right to contact, engage, interview, or hire such candidate(s) without any financial or other responsibility to the submitting agency. Unsolicited resumes, including those sent directly to hiring managers or other employees, will be considered the property of McCarthy.