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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 ...

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 ...

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 ...

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How much do hugging face jobs pay per hour?

As of Jul 28, 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.

Can you make money on Hugging Face?

Hugging Face is a platform that offers opportunities for data scientists, machine learning engineers, and developers to monetize their skills through jobs, freelance projects, or contributing to open-source models. Earning potential depends on the type of work, experience, and whether you are employed directly or working independently. Building a strong portfolio and expertise in NLP and AI tools can increase income opportunities on the platform.

Which 3 jobs will survive AI?

Jobs that require complex human interaction, creativity, and critical thinking, such as healthcare professionals, educators, and skilled tradespeople, are likely to persist despite AI advancements. These roles often involve emotional intelligence, nuanced judgment, and hands-on skills that are difficult for AI to replicate. Continuous learning and adaptability remain important for job security in an evolving technological landscape.

What are Hugging Face jobs?

Hugging Face jobs refer to employment opportunities at the company focused on developing and maintaining open-source machine learning tools, especially in natural language processing. Roles may include software engineering, research, data science, and product management, often requiring skills in Python, deep learning frameworks, and collaboration in a tech environment.

How much do Hugging Face engineers make?

Hugging Face engineers' salaries vary based on experience, role, and location, but generally range from $100,000 to $180,000 annually. Senior positions and specialized roles in machine learning or software engineering tend to offer higher compensation, often including stock options and benefits.

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 Gilbert, AZ? For Hugging Face jobs in Gilbert, AZ, the most frequently searched job titles are:
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 July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $32,048 per year, or $15.4 per hour.
AI Python Engineer

AI Python Engineer

Inficare Technologies

Phoenix, AZ • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

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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