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Hugging Face Jobs in New York (NOW HIRING)

Kasmo Inc.

Applied Ai engineer - .

Jersey City, NJ · On-site

Applied AI/ML research with LLMs & NLP RAG, Embeddings & Information Retrieval Model Evaluation & Experimentation PyTorch, Hugging Face, TensorFlow AWS AI (Bedrock/SageMaker) is a plus Banking ...

1 point system

GenAI Engineer

New York, NY · Remote

Expertise in Python and tools like Hugging Face, Langchain, and OpenAI API. Deep Learning Frameworks: Experience with TensorFlow, Keras, and PyTorch. Cloud Platforms: Familiar with Google Model ...

Spiral

Developer Relations Engineer

New York, NY · On-site

$175K - $275K/yr

Build and maintain reference pipelines against real datasets (such as those on Hugging Face), and keep them working as the product moves. * Produce credible benchmarks and the honest writeups that go ...

PSRTEK

Senior AI Security Engineer- REMOTE

New York, NY · On-site

$125K - $171K/yr

... Hugging Face) · Solid understanding of OWASP Top 10, MITRE ATT&CK, threat modeling, and SOC workflows · Deep AWS expertise, including IAM, Guard Duty, Security Hub, CloudTrail, VPC, KMS · ...

EXL

Delivery Lead

Jersey City, NJ · On-site

Hands-on experience with LLM (Large Language Models), Agentic AI, and integration with APIs from platforms like OpenAI, Hugging Face, and AWS AI services. • Data Engineering: Strong background in ...

Zealogics.com

AI Fullstack Developer

Montvale, NJ · On-site +1

$75 - $85/hr

Experience working with or integrating AI/ML models via Python, TensorFlow, PyTorch, or APIs (e.g., OpenAI, Hugging Face). * Familiarity with CI/CD pipelines, Git, and cloud services (AWS, GCP, or ...

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How much do hugging face jobs pay per hour?

As of Aug 1, 2026, the average hourly pay for hugging face in New York is $16.91, according to ZipRecruiter salary data. Most workers in this role earn between $14.18 and $20.00 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 New York? For Hugging Face jobs in New York, the most frequently searched job titles are:
What job categories do people searching Hugging Face jobs in New York look for? The top searched job categories for Hugging Face jobs in New York are:
What cities in New York are hiring for Hugging Face jobs? Cities in New York with the most Hugging Face job openings:
Hugging Face jobs near you
Infographic showing various Hugging Face job openings in New York as of July 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $35,174 per year, or $16.9 per hour.

Low-Level Senior Software Engineer, Xet Storage - US Remote

Hugging Face

New York, NY • Remote

$125K - $165K/yr

Full-time

Posted 2 days ago

New

Job description

At Hugging Face, we're on a journey to democratize good AI. We are building the fastest growing platform for AI builders with over 11 million users who collectively shared over 4 million models, 1 million datasets & 1.5 million Gradio apps. Our open-source libraries have more than 700,000 stars on Github.

About the Role

Roles at Hugging Face are very fluid and dynamic -- we're looking for someone who is comfortable taking on different challenges that evolve over time. This role sits on the Xet Storage team, the group responsible for the storage system behind all of Hugging Face. Today we store over 200PB (and growing rapidly!) of the world's most important ML & AI assets. Xet is the underlying storage architecture for the entire Hugging Face platform and community -- from the largest model repositories to the datasets and Spaces that millions of people build on every day.

In this role, you'll work across two closely connected surfaces. You'll contribute to xet-core, our open-source project written in Rust that powers hf-xet -- the Python library underpinning the Hugging Face Hub client and the wider ecosystem of open-source tools the community relies on. And you'll design, build, and operate meaningful and challenging features in the Xet Storage backend, contributing to the broader Infrastructure organization at Hugging Face. We're a small team building and operating incredible things at enormous scale, in a high-trust, low-process, async, and remote environment -- and we lean heavily on the latest AI tools to move fast.

If you love writing low-level, high-performance code and are energized by the challenge of large-scale, scalable services, this is the team for you. This usually means proven experience building and operating production systems software, but we consider every applicant on an individual basis.

Requirements

What we're looking for

  • 8+ years building and scaling distributed systems, storage, or networking infrastructure.
  • Proficiency in a low-level systems language, with Rust strongly preferred (we also work in Python, Typescript, Go, and C++ across the stack).
  • A track record of working independently in a high-trust, low-process environment -- you're comfortable with ambiguity and take ownership end to end.
  • Comfort operating in a fast-moving, async, and fully remote environment.
  • A passion for building simple, robust, and scalable systems relied on by engineering and science teams around the world.

Bonus points if you have

  • Experience designing efficient, high-performance, fault-tolerant data storage and retrieval systems.
  • Experience operating production systems -- monitoring, alerting, and distributed debugging and recovery.
  • Familiarity with git internals, cloud infrastructure (AWS, Azure, GCP, Kubernetes), databases (relational and non-relational), or networking.

About You

If you love open-source, are excited by the intersection of low-level performance work and large-scale services, and want your code to sit at the foundation of the world's largest platform for AI builders, then we can't wait to see your application!

If you're interested in joining us, but don't tick every box above, we still encourage you to apply! We're building a diverse team whose skills, experiences, and backgrounds complement one another. We're happy to consider where you might be able to make the biggest impact.

One more thing

At Hugging Face we believe great AI shouldn't require a massive cluster, we build for everyone, especially the GPU-poor. And because we read every application, here's a small sign that you read this one too: start your answer to the first application question with the words “GPU-poor and proud