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Hugging Face Jobs in Arizona (NOW HIRING)

Arkhya Tech

GenAI Solutions Leader

Phoenix, AZ · On-site

Hands-on with GenAI and agentic AI (LLMs, diffusion models, RAG, tool use/agents); familiarity with OpenAI Azure, Hugging Face, LangChain/LangGraph, ADK, vector databases. Experience with MLOps ...

Forhyre

Prompt Engineers

Phoenix, AZ

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 ...

Tata Consultancy Service Limited

AI Engineer

Phoenix, AZ · On-site

$100K - $120K/yr

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

Apptad Inc

Senior AI Engineer at Phoenix, AZ

Phoenix, AZ · On-site

$55 - $60/hr

Experience with Hugging Face, PyTorch, or ML model deployment * Contributions to AI/ML or open-source projects What Makes This Role Unique * Work on cutting-edge Agentic AI systems * High ownership ...

Tata Consultancy Service Limited

AI Engineer

Phoenix, AZ · On-site

$100K - $120K/yr

... Hugging Face ecosystem (embeddings, fine-tuning, inference tooling), with some exposure to TensorFlow • Strong schema, validation, and state management practices using tools such as Pydantic ...

Inficare Technologies

Lead AI Engineer

Phoenix, AZ · 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 ...

Microchip Technology

Engineer I-Software

Chandler, AZ · On-site

Experience working with LLM APIs (OpenAI, Hugging Face, etc.). What You'll Gain: * Mentorship from senior full stack and AI engineers. * Real-world experience building production-grade applications.

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How much do hugging face jobs pay per hour?

As of Jun 27, 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.

Which 3 jobs will survive AI?

Jobs that require complex human interaction, creativity, and critical thinking, such as healthcare professionals, software developers, and educators, are likely to persist despite AI advancements. These roles often involve emotional intelligence, nuanced decision-making, and specialized skills that are difficult for AI to replicate. Continuous learning and adaptability are essential for job security in an evolving AI landscape.

What job makes $10,000 a month without a degree?

High-paying roles that can earn $10,000 a month without a degree include skilled trades such as commercial diving, certain sales positions like real estate or software sales, and specialized tech roles like web development or cybersecurity, which often value skills and certifications over formal education. Success in these jobs typically requires experience, technical skills, or industry certifications, and they may involve self-employment or freelance work.

What jobs pay $2000 a day?

High-paying jobs that can pay around $2000 a day often include specialized roles such as senior software engineers, data scientists, management consultants, and certain freelance or contract positions in finance, law, or technology. These roles typically require advanced skills, extensive experience, and sometimes certifications, and may involve project-based or consulting work with flexible schedules.

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.

How much does Hugging Face pay?

Salaries at Hugging Face vary depending on the role, experience, and location, but the company generally offers competitive compensation for AI and machine learning positions. Entry-level roles may start around $80,000 annually, while more experienced engineers and researchers can earn over $150,000 per year. Benefits often include flexible schedules, remote work options, and opportunities to work with cutting-edge NLP tools.
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:
Hugging Face jobs near you
Infographic showing various Hugging Face job openings in Arizona as of June 2026, with employment types broken down into 9% As Needed, 61% Full Time, 6% Part Time, 3% Temporary, 18% Contract, and 3% Nights. Highlights an 73% Physical, 4% Hybrid, and 23% Remote job distribution, with an average salary of $29,961 per year, or $14.4 per hour.
GenAI Solutions Leader

GenAI Solutions Leader

Arkhya Tech

Phoenix, AZ • On-site

Other

Posted yesterday

Job description

AI Evangelist/AI Expert/ GenAI Solutions Leader

Location : Phoenix AZ - Onsite

Full-Time

Lead platform releases, feature rollouts, and adoption initiatives in partnership with product and engineering teams.

o Architect and execute go to market strategies spanning onboarding, training, documentation, and ongoing support.

Customer Enablement & Training o Conduct workshops, office hours, and hands on pair programming while maintaining self service resources (SDKs, guides, playbooks) to drive adoption and reduce time to value. o Create scalable enablement assets and tailor training approaches based on a deep understanding of customer workflows and pain points.

Solution Strategy & Feedback Loop o Establish tight feedback loops with end users to surface insights that shape roadmap direction, influence implementation, and drive usability improvements. o Translate business problems into actionable solution architectures partnering with platform teams on patterns, reusable accelerators, acceptance criteria, and reference architectures to standardize solution delivery.

o Stay current with industry trends in MLOps/LLMOps, GenAI, agentic frameworks, and cloud optimization.

Stakeholder Relationship & Communication o Build

Required Qualifications:

4+ years of Artificial Intelligence experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

3+ years across product/solution management, program delivery, or technical product ownership for AI/ML platforms, or cloud-native solutions.

3+ years hands-on with cloud technologies (Google Cloud Platform, or Azure) and container orchestration (Docker, Kubernetes/OpenShift). Desired Qualifications

5+ years across the AI/ML lifecycle: data management, feature engineering, model development, deployment, monitoring/observability, and model risk/governance.

Experience in large enterprise environments (regulated industries preferred) and building platforms at scale.

Hands-on with GenAI and agentic AI (LLMs, diffusion models, RAG, tool use/agents); familiarity with OpenAI Azure, Hugging Face, LangChain/LangGraph, ADK, vector databases.

Experience with MLOps/LLMOps tooling and practices (model registry, CI/CD, feature store, prompt/chain/versioning, evaluation, guardrails, monitoring).

Strong communication skills with the ability to influence senior stakeholders and simplify complex technical

Regards,

Bhupendra

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