ZipRecruiter

Log In

1

Hugging Face Jobs in Seattle, WA (NOW HIRING)

SpangleAI

AI/ML Scientist

Bellevue, WA · On-site

Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, Hugging Face , and libraries focused on GAI/LLM development * Familiarity with data warehouse and data pipeline ...

HC1316 GE Precision Healthcare LLC

AI Engineer

Bellevue, WA · On-site

$160 - $240/hr

AI Infrastructure Experience with modern AI frameworks such as PyTorch, Hugging Face, DeepSpeed, Megatron, or PyTorch Lightning. Experience deploying AI workloads using MLOps, ModelOps, or Foundation ...

New

Launch Consulting

Sr. Data Scientist

Bellevue, WA · On-site

$140K - $180K/yr

Deep expertise in Python, including libraries such as scikit-learn, pandas, NumPy, TensorFlow, PyTorch, spaCy, and/or Hugging Face. * Strong understanding of statistical modeling, regression ...

Geico

Senior Engineer - Applied AI

Seattle, WA · On-site

$118K - $163K/yr

Strong experience with Python and modern AI frameworks such as LangChain, LangGraph, LangSmith, LlamaIndex, Hugging Face, and OpenAI or Anthropic APIs. * Production AI delivery: Demonstrated ...

Tata Consultancy Services

AI Enterprise Architect

Seattle, WA · On-site

$78.50 - $101.25/hr

TensorFlow, PyTorch, Hugging Face, NLP, computer vision, time-series modeling • AI Strategy, Architecture, and Roadmap Planning • Python / R / TypeScript Programming • AI Frameworks (LangChain ...

Geico

Sr. Software Engineer - Applied AI

Seattle, WA · On-site

$139K - $183K/yr

Strong experience with Python and modern AI frameworks such as LangChain, LangGraph, LangSmith, LlamaIndex, Hugging Face, and OpenAI or Anthropic APIs. * Production AI delivery: Demonstrated ...

previous pagenext page

Showing results 21-40

All JobsHugging Face JobsHugging Face Jobs in Seattle, WA

Hugging Face information

See Seattle, WA salary details

$10

$17

$23

How much do hugging face jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for hugging face in Seattle, WA is $17.60, according to ZipRecruiter salary data. Most workers in this role earn between $14.76 and $20.82 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 Seattle, WA?

For Hugging Face jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Hugging Face jobs in Seattle, WA look for?

The top searched job categories for Hugging Face jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Hugging Face jobs?

Cities near Seattle, WA with the most Hugging Face job openings:

Hugging Face jobs near you
Infographic showing various Hugging Face job openings in Seattle, WA as of August 2026, with employment types broken down into 79% Full Time, 18% Part Time, and 3% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $36,609 per year, or $17.6 per hour.

AI/ML Scientist

SpangleAI

Bellevue, WA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 17 days ago

Job description

About SpangleAI
Launched in 2025, Spangle AI is the agentic conversion layer connecting AI-led discovery to real-time conversion. We've partnered with enterprise brands like REVOLVE, Alexander Wang, and Steve Madden, delivering up to 50% conversion lifts and 2x ROAS improvements.
We recently closed a $15M Series A. Spangle won NRF's VIP (Vendor in Partnership) Award for Best AI-Driven Marketing Solution and was recognized in Business of Fashion's AI startups to Watch.
Founded by serial entrepreneurs with 30+ years scaling AI and commerce at Amazon, Saks, and Gap, we're building the commerce infrastructure for the agentic era, where ChatGPT Shopping, Google AI Overviews, and Meta are reshaping how consumers discover and buy.
The Role
We are seeking a ML Scientist that will be responsible for building GAI/LLM models end-to-end, from developing the data pipeline to model deployment, to solving real-world problems in the e-commerce sector. You will also collaborate with cross-functional teams to deliver solutions that delight our customers and shoppers.
This role is preferably based in Seattle, the Bay Area, or Austin. Join our founding team to drive product innovation and contribute directly to the growth of our dynamic startup.
What you'll own:
  • AI/ML Research and Innovation: Conduct cutting-edge research in Generative AI (GAI) and Large Language Models (LLMs), staying at the forefront of AI/ML advancements. Identify and explore novel algorithms, architectures, and techniques to enhance model performance, scalability, and efficiency in e-commerce applications
  • Implementation: Train, deploy, and optimize GAI and LLM algorithms and models to improve product recommendations, search relevance, personalization, and customer interaction
  • Data Engineering: Design, build, and manage ETL processes to gather data from various sources, transform it into a usable format, and load it into a data warehouse or data lake
  • Delivery: Collaborate with product, engineering, and data teams to identify opportunities for applying generative AI and LLMs to solve complex problems and enhance customer experiences
  • Evaluation: Design and conduct experiments to evaluate the performance and effectiveness of generative and language models in an e-commerce context

What We're Looking For
Education
  • Ph.D. or Master's degree in AI, Machine Learning, Data Science, Computer Science, Electrical Engineering, Statistics, or a related field with a focus on artificial intelligence

Experience
  • 2-5 years of experience, proven experience in developing and deploying AI applications end to end in real-world applications, preferably in e-commerce or a related field

Technical Skills
  • Deep expertise in generative models (e.g., GANs, diffusion models, autoencoders) and Large Language Models (e.g., GPT, BERT, T5, LLaMA)
  • Experience with LLM fine-tuning, RL post training, prompt engineering, and deploying LLMs for applications such as natural language understanding, content generation, and recommendation systems
  • Strong understanding of the architecture and training techniques for transformer-based models, attention mechanisms, and optimization strategies for LLMs
  • Expertise in distributed training of large-scale models, including using parallelization and optimization techniques for handling large datasets
  • Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, Hugging Face, and libraries focused on GAI/LLM development
  • Familiarity with data warehouse and data pipeline technologies (e.g., Amazon Redshift, Google BigQuery, Snowflake, Apache Airflow)
  • Knowledge of cloud platforms and services (e.g., AWS, Google Cloud, Azure) for deploying and scaling machine learning models, especially those involving LLMs and GAI
  • Understanding of reinforcement learning and its applications within generative AI and LLMs for decision-making, personalization, or conversational AI systems.

Our Culture
  • GenAI-native in how we build, sell, and operate
  • High ownership, low overhead, and bias toward action
  • Focus on speed, experimentation, and execution
  • Deep emphasis on creating clear, demonstrable customer value
  • Preference for builders and operators over hierarchy
  • Strong belief in in-person collaboration

Why Spangle
  • Meaningful ownership and impact at an early stage with ample career growth opportunities
  • Competitive salary with uncapped commission and equity
  • Benefits: Health, dental, and vision insurance, 401(k), Unlimited PTO

Apply