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Huggingface Jobs in California (NOW HIRING)

Liquid AI, Inc

ICML 2026

San Francisco, CA · On-site +1

$69K - $70K/yr

Open-source contributions (code, data, or models) on GitHub or HuggingFace. * Experience deploying models to edge or on-device environments. What We Offer * Full ownership: You own your work from ...

Turing

Client Director, Frontier Data - US

Palo Alto, CA · On-site

$255K - $325K/yr

Familiarity with ML tools and data workflows (e.g., HuggingFace, LangChain, Weights & Biases, Databricks) Preferred Qualifications * Experience evaluating large language model performance and/or ...

Prime Intellect

Head of Growth

San Francisco, CA · On-site

$150/hr

Own Your Intelligence Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. Our platform, Lab ...

Cloudera, Inc.

Staff Software Engineer - AI

San Jose, CA · On-site

$184K - $230K/yr

Experience with HuggingFace, Nvidia AI frameworks and Nim models. * Experience with AI/ML orchestration software KServe, Knative, Kubeflow. * Experience with building AI applications with machine ...

Cloudera

Staff Software Engineer - AI

San Jose, CA · Hybrid

$184K - $230K/yr

Experience with HuggingFace, Nvidia AI frameworks and Nim models. * Experience with AI/ML orchestration software KServe, Knative, Kubeflow. * Experience with building AI applications with machine ...

Scale AI

Frontier Agents Engineer

San Francisco, CA · On-site

... HuggingFace, OpenAI API) • Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure • Strong problem-solving skills with the ability to navigate ambiguous requirements ...

Cloudera

Staff Software Engineer - AI

San Jose, CA · On-site

$184K - $230K/yr

Experience with HuggingFace, Nvidia AI frameworks and Nim models. * Experience with AI/ML orchestration software KServe, Knative, Kubeflow. * Experience with building AI applications with machine ...

GenBio AI

Product Engineer

Palo Alto, CA

$170K - $260K/yr

Familiarity with AI model serving frameworks such as Triton Inference Server, HuggingFace Transformers/Spaces, or Gradio * Prior work with GPU-accelerated tools (e.g., CUDA, cuDNN, Triton)

Cloudera

Staff Software Engineer - AI

San Jose, CA · On-site

$184K - $230K/yr

Experience with HuggingFace, Nvidia AI frameworks and Nim models. * Experience with AI/ML orchestration software KServe, Knative, Kubeflow. * Experience with building AI applications with machine ...

Cloudera

Staff Software Engineer - AI

San Jose, CA · Hybrid

$184K - $230K/yr

Experience with HuggingFace, Nvidia AI frameworks and Nim models. * Experience with AI/ML orchestration software KServe, Knative, Kubeflow. * Experience with building AI applications with machine ...

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How much do huggingface jobs pay per hour?

As of Jul 13, 2026, the average hourly pay for huggingface in California is $25.79, according to ZipRecruiter salary data. Most workers in this role earn between $14.83 and $30.13 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Huggingface position, and why are they important?

To thrive in a role at Hugging Face, you typically need strong skills in machine learning, natural language processing (NLP), and software development, supported by a relevant degree in computer science or a related field. Familiarity with frameworks like PyTorch or TensorFlow, plus experience using version control systems such as Git, are often required; open-source contributions and cloud platform knowledge are a plus. Excellent communication, collaborative teamwork, and problem-solving abilities help candidates stand out in this dynamic, innovation-driven environment. These strengths are crucial because they enable individuals to develop high-impact AI tools, work effectively in interdisciplinary teams, and contribute to open-source communities.

What does a typical day look like for an engineer working at Hugging Face?

As an engineer at Hugging Face, your day typically involves collaborating with team members to design, develop, and improve state-of-the-art machine learning models and tools, with a strong focus on open-source NLP projects. You’ll participate in code reviews, experiment with new technologies, engage with the community through forums or GitHub, and help support user questions or issues. Expect a fast-paced, collaborative environment where cross-functional teamwork with product managers, researchers, and other engineers is common. The work is project-driven, with plenty of opportunities to contribute ideas, learn from experts, and advance your technical skills.

What is a Huggingface job?

A Hugging Face job typically refers to a role at Hugging Face, a company specializing in machine learning and natural language processing (NLP). Employees at Hugging Face work on developing and maintaining open-source AI tools, including the popular Transformers library. Roles range from research and engineering to product and community development, often focusing on advancing state-of-the-art AI models.

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Huggingface jobs near you
Infographic showing various Huggingface job openings in California as of July 2026, with employment types broken down into 1% Internship, 95% Full Time, 3% Part Time, and 1% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution, with an average salary of $53,653 per year, or $25.8 per hour.
ICML 2026

ICML 2026

Liquid AI, Inc

San Francisco, CA • On-site, Remote

$69K - $70K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

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

Job description

About Liquid AI
Spun out of MIT CSAIL, we build foundation models from scratch using a fundamentally different architecture. Our Liquid Foundation Models (LFMs) are built on a fundamentally different hybrid architecture; they deliver faster inference, lower memory, and deploy where traditional models can't. We ship open-weight text, vision-language, and audio-language models that run on phones, laptops, vehicles, and embedded devices.
Why We're at ICML
We're here because ICML brings together the people working on the problems we care most about: efficient architectures, representation learning, multimodal reasoning, and the science of how models learn. If our conversation at the booth was interesting, this is the next step.
What We're Building
Liquid AI is hiring across several research and engineering areas. You don't need to fit neatly into one. If your work touches any of these, we want to talk:
  • Efficient Architectures. State space models, hybrid attention designs, neural ODEs, and alternatives to the transformer paradigm. Our LFM2 architecture combines gated short convolutions with grouped query attention. We're looking for people who think about what comes next.
  • Multimodal Vision. Vision-language models that run on-device under tight latency and memory constraints. Our VLM team has shipped multiple best-in-class models and owns the full pipeline from architecture through deployment.
  • Multimodal Audio. Speech foundation models, end-to-end audio-language systems, and real-time voice on constrained hardware. Our LFM2.5-Audio runs natively on devices with dramatically faster decoding than its predecessor.
  • Data Engineering. Pre-training data curation, synthetic data generation, data mixtures, and scaling strategies. The quality of what goes in determines everything that comes out.
  • Infrastructure & Performance. Distributed training, GPU kernel optimization, edge inference, and model serving at scale. We build the systems that make our architecture fast in practice, from custom kernels to on-device deployment pipelines.
  • Post-Training & Alignment. RLHF, preference optimization, multi-stage reinforcement learning, and evaluation. Our latest models were shaped by large-scale RL without supervised fine-tuning warmup.

Who Thrives Here
This is a small team where individuals own entire work-streams end-to-end, from research through shipped models. We publish. We release open weights. We present at the conferences you attend. If you want to do work that is visible and that ships, this is the environment for it.
What We're Looking For
  • Demonstrated research or engineering contribution in one or more of the areas above.
  • Ability to move from idea to implementation to shipped result.
  • M.S. or Ph.D. in Computer Science, Mathematics, Electrical Engineering, or a related field; or equivalent industry experience.

Stronger candidates will also have:
  • Published research at top-tier venues (NeurIPS, ICML, ICLR, CVPR, ACL, Interspeech, etc.).
  • Experience training or fine-tuning foundation models at scale.
  • Hands-on work with distributed training infrastructure (DeepSpeed, FSDP, Megatron-LM).
  • Open-source contributions (code, data, or models) on GitHub or HuggingFace.
  • Experience deploying models to edge or on-device environments.

What We Offer
  • Full ownership: You own your work from architecture to deployment.
  • Compensation: Competitive base salary with equity in a unicorn-stage company.
  • Health: We pay 100% of medical, dental, and vision premiums for employees and dependents.
  • Financial: 401(k) matching up to 4% of base pay.
  • Time Off: Unlimited PTO plus company-wide Refill Days throughout the year.
  • Visa Sponsorship: We sponsor O-1 and H-1B visas for exceptional talent. If you can't relocate, we'll find a way to work together.

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