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Hugging Face Jobs in Missouri (NOW HIRING)

Fractal Analytics Ltd.

Data Scientist_5

California, MO · On-site

$150 - $170/hr

Strong experience working with LLMs (e.g., GPT‑4, LLaMA, Claude, PaLM) and frameworks such as Hugging Face, LangChain, LlamaIndex, or Haystack. * Experience implementing agent‑based architectures ...

Jobgether

$80K - $110K/yr

Hands-on experience with open-source AI frameworks such as Hugging Face Transformers. * Proven experience deploying AI models on GPU infrastructure. * Strong Python backend development skills for AI ...

MasterCard

Senior AI Engineer

O Fallon, MO · Hybrid

$97K - $134K/yr

OpenAI, Anthropic, Gemini, Hugging Face, LangChain/LangGraph, and open-source foundation models (LLaMA, Mistral, Falcon, etc.). Strong command of Gen AI engineering patterns: prompt engineering ...

Jobgether

$48.50 - $64/hr

Hands-on experience with machine learning frameworks such as PyTorch, JAX, TensorFlow, Hugging Face, or similar technologies. * Strong knowledge of cloud infrastructure, DevOps practices, and modern ...

Walmart

Staff, Software Engineer - Python/GenAI

Noel, MO · On-site

$110K - $220K/yr

Experience working with or integrating open-source and/or commercial GenAI libraries/frameworks such as Hugging Face Transformers, LangChain, OpenAI API , or similar. * Ability to productionize and ...

MasterCard

Senior Software Engineer

O Fallon, MO

$114K - $151K/yr

... Hugging Face) for model development, tuning, or serving Core Engineering Skills Strong Java engineering expertise, including designing, developing, testing, and maintaining scalable, high-performance ...

Mastercard, Inc.

Senior Software Engineer

O Fallon, MO · On-site

$114K - $151K/yr

... Hugging Face) for model development, tuning, or serving Core Engineering Skills • Strong Java engineering expertise, including designing, developing, testing, and maintaining scalable, high ...

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How much do hugging face jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for hugging face in Missouri is $14.50, according to ZipRecruiter salary data. Most workers in this role earn between $12.16 and $17.12 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 Missouri? For Hugging Face jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Hugging Face jobs in Missouri look for? The top searched job categories for Hugging Face jobs in Missouri are:
What cities in Missouri are hiring for Hugging Face jobs? Cities in Missouri with the most Hugging Face job openings:
Hugging Face jobs near you
Infographic showing various Hugging Face job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 17% Part Time, and 4% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $30,157 per year, or $14.5 per hour.

Manager, Machine Learning Engineering - Ad Platforms

Jobtailor

California, MO • On-site

$180 - $260/hr

Other

Posted 5 days ago

Job description

Responsibilities
  • Lead, mentor and guide Data Scientists, Machine Learning and AI engineers to build solutions adhering to industry best practices and deliver scalable solutions including model architecture and algorithm selection.
  • Lead by example and always strive to improve the design for more scalable, cleaner, and decoupled implementations.
  • Drive adoption of best practices in model development, code quality, testing, and documentation.
  • Have a solid understanding and usage of automated tools (AI) while adhering to company policy.
  • Define strategic direction for machine learning projects and collaborate with product and engineering stakeholders.
  • Oversee end‑to‑end machine learning workflow, including data collection, model development, deployment and modeling.
  • Foster innovation by exploring new ML techniques, tools, and technologies.
  • Communicate strategies, progress, and results to leadership and cross‑functional teams.
  • Ensure responsible AI practices, including fairness, explainability, and compliance with privacy and ethical standards.
  • Develop partnerships across the organization to identify and prioritize high‑impact ML opportunities.
  • Be available for on‑call rotations based on the team’s escalation policy and support schedule for ML/AI solutions.
Requirements
  • Bachelor’s or master’s degree in computer science, engineering, mathematics, statistics, or a related field.
  • 8+ years of relevant industry experience, with at least 2‑3 years in a people‑management or technical leadership role.
  • Proven ability to translate business problems into scalable ML and GenAI solutions and a strong understanding of machine learning fundamentals, deep learning, and statistical modeling.
  • Proven experience designing, building, and deploying scalable machine learning models and systems in production.
  • Experience deploying ML/GenAI systems at scale using cloud platforms and MLOps practices.
  • Advanced programming proficiency (e.g., Python, Java, or similar); experience with ML/DL frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face).
  • Experience building, fine‑tuning, evaluating, and deploying LLM‑based systems (e.g., RAG, prompt engineering, model optimization).
  • Demonstrated ability to lead global teams and collaborate across organizational boundaries.
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