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Hugging Face Jobs in Florida (NOW HIRING)

Python Developer (AI/LLM Specialist)

Tampa, FL ยท On-site

$45.75 - $63/hr

Integrate and fine-tune LLMs (OpenAI, Anthropic, Hugging Face, Mistral, and other open-source models) . * Apply advanced prompt engineering, RAG (retrieval-augmented generation), chain-of-thought ...

Sr Python Developer

Thonotosassa, FL ยท On-site

$109K - $147K/yr

Expertise in PyTorch or TensorFlow, plus libraries like Scikit-learn, Keras, and Hugging Face. Ollma. Data Handling: Mastery of SQL, NoSQL, Pandas, NumPy, and preprocessing tools. Generative AI LLMs:

Python Developer

Tampa, FL ยท On-site

$45.75 - $63/hr

Expertise in PyTorch or TensorFlow, plus libraries like Scikit-learn, Keras, and Hugging Face. Data Handling: Mastery of SQL, NoSQL, Pandas, NumPy, and preprocessing tools. Generative AI LLMs:

Python Developer

Thonotosassa, FL ยท On-site

$45.25 - $62.50/hr

Expertise in PyTorch or TensorFlow, plus libraries like Scikit-learn, Keras, and Hugging Face. Ollma. Data Handling: Mastery of SQL, NoSQL, Pandas, NumPy, and preprocessing tools. Generative AI ...

Utilize tools like OpenAI API, Hugging Face, LangChain, LlamaIndex, and cloud platforms (AWS, Azure, GCP) for AI development and deployment. Required: ยท 5+ years of experience in AI/ML engineering ...

Utilize tools like OpenAI API, Hugging Face, LangChain, LlamaIndex, and cloud platforms (AWS, Azure, GCP) for AI development and deployment. Required: โ€ข 5+ years of experience in AI/ML engineering ...

Expertise in PyTorch or TensorFlow, plus libraries like Scikit-learn, Keras, and Hugging Face. Ollma. Data Handling: Mastery of SQL, NoSQL, Pandas, NumPy, and preprocessing tools. Generative AI LLMs:

Python Developer, Node Exp.

Tampa, FL ยท On-site

$45.75 - $63/hr

Expertise in PyTorch or TensorFlow, plus libraries like Scikit-learn, Keras, and Hugging Face. Ollma. Data Handling: Mastery of SQL, NoSQL, Pandas, NumPy, and preprocessing tools. Generative AI LLMs:

Heavy hands-on experience with PyTorch, Hugging Face, and orchestration layers like LangChain, LlamaIndex, or equivalent frameworks * Vector and Retrieval Mastery: Direct experience engineering ...

Senior AI Application Engineer

Tampa, FL ยท On-site +1

$120K - $140K/yr

Deep hands-on experience with LLM frameworks -- LangChain, LangGraph, LlamaIndex, OpenAI/Anthropic SDKs, Hugging Face; able to reason about trade-offs across them. * Demonstrated experience building ...

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How much do hugging face jobs pay per hour?

As of Jul 4, 2026, the average hourly pay for hugging face in Florida is $11.55, according to ZipRecruiter salary data. Most workers in this role earn between $9.71 and $13.65 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 cities in Florida are hiring for Hugging Face jobs? Cities in Florida with the most Hugging Face job openings:

Python Developer (AI/LLM Specialist)

Purple Drive

Tampa, FL โ€ข On-site

$45.75 - $63/hr

Other

Posted 12 days ago


Job description

Overview:
Python Developer (AI/LLM Specialist)
Location: Tampa, FL - Onsite
Type: Contract
Role Overview
We are seeking a highly skilled Python Developer with expertise in AI, LLM integration, and agentic frameworks. The ideal candidate will design, build, and deploy advanced multi-agent AI systems, reasoning pipelines, and task automation flows, while ensuring scalability and performance. This role also requires leadership skills to mentor junior developers, guide project scoping, and align with cross-functional stakeholders.
Key Responsibilities
  • Develop and maintain Python applications leveraging modern frameworks (asyncio, FastAPI/Flask, multiprocessing).
  • Design and implement AI-driven agentic systems using LangChain, LangGraph, LlamaIndex, Haystack, Semantic Kernel, AutoGen, and similar frameworks.
  • Integrate and fine-tune LLMs (OpenAI, Anthropic, Hugging Face, Mistral, and other open-source models).
  • Apply advanced prompt engineering, RAG (retrieval-augmented generation), chain-of-thought orchestration, tool use, and function calling to optimize AI system performance.
  • Architect scalable reasoning pipelines and task automation flows.
  • Implement containerization and deployment with Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure), including GPU optimization.
  • Drive model evaluation strategies and best practices for Model Ops.
  • Mentor team members, provide technical leadership, and ensure alignment across cross-functional teams.
Required Skills & Experience
  • 8+ years of professional Python development experience.
  • Proven expertise in agentic frameworks (LangChain, LangGraph, LlamaIndex, Haystack, Semantic Kernel, AutoGen, etc.).
  • Strong background in LLM integration: fine-tuning, RAG, prompt engineering, orchestration, and tool/function usage.
  • Hands-on experience with Hugging Face Transformers, OpenAI APIs, Anthropic, Mistral, and open-source models.
  • Proficiency in FastAPI/Flask, asyncio, multiprocessing.
  • Deployment experience with Docker, Kubernetes, GPU optimization, and cloud platforms (AWS/GCP/Azure).
  • Strong system design skills for multi-agent systems and reasoning pipelines.
  • Excellent leadership, mentorship, and project scoping abilities.
Nice to Have
  • Research or implementation experience with emerging LLM/AI agent frameworks.
  • Prior experience in large-scale AI/ML deployments in production environments.
  • Contributions to open-source AI/ML projects.