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Hugging Face Jobs in Gilbert, AZ (NOW HIRING)

Inficare Technologies

AI Python Engineer

Phoenix, AZ · On-site

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 ...

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 ...

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 ...

Vaco LLC

Staff / Principal AI Engineer

Gilbert, AZ · On-site

$170K - $190K/yr

... Hugging Face, Snowflake, and modern ML or analytics tooling Experience designing AI or ML solutions in Azure or comparable cloud environments Experience with CI/CD pipelines, Docker, Kubernetes ...

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How much do hugging face jobs pay per hour?

As of Aug 26, 2026, the average hourly pay for hugging face in Gilbert, AZ is $15.41, according to ZipRecruiter salary data. Most workers in this role earn between $12.93 and $18.22 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 job categories do people searching Hugging Face jobs in Gilbert, AZ look for?

The top searched job categories for Hugging Face jobs in Gilbert, AZ are:

What cities near Gilbert, AZ are hiring for Hugging Face jobs?

Cities near Gilbert, AZ with the most Hugging Face job openings:

Hugging Face jobs near you
Infographic showing various Hugging Face job openings in Gilbert, AZ as of August 2026, with employment types broken down into 81% Full Time, 16% Part Time, and 3% Contract. Highlights an 88% Physical, 1% Hybrid, and 11% Remote job distribution, with an average salary of $32,048 per year, or $15.4 per hour.

AI Python Engineer

Inficare Technologies

Phoenix, AZ • On-site

Full-time

Re-posted 4 days ago

Job description

Job Title: Senior AI Python Engineer
Location: Phoenix, AZ (Hybrid - 3 days onsite)
Job Type: Long-Term Contract
Experience: 10+ years
Job Overview
We are looking for a Senior Engineer - Artificial Intelligence to design and build impactful, intelligent, and secure AI solutions in the Information Security, Governance, and Control space. You will translate complex business requirements into scalable, production-ready AI applications using cutting-edge Generative AI and agentic frameworks.
Key Responsibilities
  • Build and enhance AI/ML and GenAI-powered solutions using Python, LLMs, RAG, prompt engineering, and agentic AI frameworks
  • Develop models for NLP, classification, clustering, anomaly detection, and predictive analytics
  • Support model lifecycle activities: experimentation, evaluation, versioning, deployment, monitoring, and documentation
  • Contribute to cloud-native ML pipelines and AI application deployment using MLOps, APIs, Docker, and Kubernetes
  • Collaborate cross-functionally with Security, Risk, Engineering, Governance, and Data teams
  • Stay current with emerging trends in Machine Learning, Generative AI, Agentic AI, and MLOps
Required Skills
  • Strong Python programming with frameworks such as PyTorch, TensorFlow, or scikit-learn
  • Hands-on experience with LLMs, NLP, embeddings, RAG, and prompt engineering
  • Experience with agentic AI frameworks: LangChain, LangGraph, AutoGen, or CrewAI
  • Exposure to APIs, cloud platforms (AWS, Azure, GCP), Docker, Kubernetes, and vector databases
  • MLOps/data tools: MLflow, Kubeflow, Argo Workflows, Kafka, Spark, or NiFi
Preferred Skills
  • 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 onsite per week)
Engagement Details
Long-term contract engagement. Bachelor's degree in Computer Science, Engineering, Data Science, AI, or a related field required.

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