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Hugging Face Jobs (NOW HIRING)

Cloud ML DevRel Engineer - US remote

New York, NY · On-site +1

$61 - $81.50/hr

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 ...

Cloud ML DevRel Engineer - US remote

New York, NY · On-site +1

$61 - $81.50/hr

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 ...

If you don't see the perfect job position, just apply to this one - we'll brainstorm to put you in position to do the best work of your life at Hugging Face! Requirements * You're deeply passionate ...

Senior AI/ML Engineer

Indianapolis, IN

$99.90K - $137.20K/yr

... Hugging Face transformers and fine-tuned models into ETL and downstream applications. • Build and manage robust ETL workflows using Spark, Glue, Airflow, or similar; handle structured/unstructured ...

Hugging Face, LangChain, Open AI API. * RAG pipelines: use Hugging Face, LangChain, and Open AI API to architect RAG pipelines and integrate generative AI into enterprise cloud environments. * Strong ...

Senior AI/ML Engineer

Indianapolis, IN

$99.90K - $137.20K/yr

... Hugging Face transformers and fine-tuned models into ETL and downstream applications. • Build and manage robust ETL workflows using Spark, Glue, Airflow, or similar; handle structured/unstructured ...

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How much do hugging face jobs pay per hour?

As of Jun 3, 2026, the average hourly pay for hugging face in the United States is $15.46, according to ZipRecruiter salary data. Most workers in this role earn between $12.98 and $18.27 per hour, depending on experience, location, and employer.

What professions make 500,000 a year?

Professions that can earn $500,000 or more annually include senior roles such as CEOs, investment bankers, specialized surgeons, and successful entrepreneurs. High earnings often require extensive experience, advanced skills, and often involve leadership or highly specialized knowledge in their fields.

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.

More about Hugging Face jobs
What cities are hiring for Hugging Face jobs? Cities with the most Hugging Face job openings:
What states have the most Hugging Face jobs? States with the most job openings for Hugging Face jobs include:
Infographic showing various Hugging Face job openings in the United States as of May 2026, with employment types broken down into 97% Part Time, and 3% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $32,151 per year, or $15.5 per hour.
Cloud ML DevRel Engineer - US remote

Cloud ML DevRel Engineer - US remote

Hugging Face

New York, NY • On-site, Remote

$61 - $81.50/hr

Full-time

Medical, Dental, Vision, PTO

Posted 23 days ago


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 2M models, 700k datasets & 600k apps. Our open-source libraries have more than 600k+ stars on Github.

About the Role

As a Cloud ML DevRel Engineer, your goal will be to increase the impact of the Hugging Face ML Cloud team by educating the community of ML practitioners on how they can benefit by accelerating their training and inference workloads.

The Hugging Face ML Cloud team is working through strategic collaborations with the most used Clouds (AWS, GCP, Azure, Cloudflare), AI Accelerators (incl. NVIDIA, AMD, Intel, Gaudi, Inferentia, TPU), and Systems (Dell, Nutanix), to make it easy for the community to use Hugging Face models and libraries on these compute platforms.

These partnerships are core to Hugging Face product strategy as an open platform (no lock-in of customers), and monetization strategy to drive usage and revenue for our partners through commercial collaborations and product extensions.

This is a solid engineering role with a flavor of education and community. Your impact will be driving visibility and usage of integrations with strategic partners, through activities including:

  • Publishing technical blog posts
  • Contributing documentation and code examples
  • Speaking to business and technical audiences at partner conferences,
  • Participating in, or producing webinars
  • Building and evangelizing demos
  • Leading GTM conversations with strategic partners.

You will be at the forefront of Generative AI (and how to build practical stuff with open source). You will work hand in hand with the most important companies in AI. You will enjoy a lot of autonomy and full creative control, with the goal to have 10x more impact than a similar role at a big tech corporation.

About You

You are passionate about ML Engineering, building practical AI applications, putting them in production, and accelerating them to the best of the Cloud ability. You love learning new challenging engineering concepts and technologies, and discussing them with engineers. You appreciate a good Developer Experience, and take pride in your code being easy to understand.

You are a great communicator and educator, comfortable (as much as one can be!) with public speaking to technical audiences.

You like to move fast with high autonomy and experiment with new ways to ship things. You are exposed to cloud ML ecosystem,

You love engaging with the ML community in a positive and helpful way. Existing engagement in social platforms (GitHub, LinkedIn, Twitter, Reddit, etc) or other communication/education channels is expected. Having experience in Open Source development will be helpful..

More about Hugging Face

We are actively working to build a culture that values diversity, equity, and inclusivity.We are intentionally building a workplace where people feel respected and supported-regardless of who you are or where you come from. We believe this is foundational to building a great company and community. Hugging Face is an equal opportunity employer and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

We value development.You will work with some of the smartest people in our industry. We are an organization that has a bias for impact and is always challenging ourselves to continuously grow. We provide all employees with reimbursement for relevant conferences, training, and education.

We care about your well-being. We offer flexible working hours and remote options. We offer health, dental, and vision benefits for employees and their dependents. We also offer parental leave and flexible paid time off.

We support our employees wherever they are. While we have office spaces in NYC and Paris, we're very distributed and all remote employees have the opportunity to visit our offices. If needed, we'll also outfit your workstation to ensure you succeed.

We want our teammates to be shareholders. All employees have company equity as part of their compensation package. If we succeed in becoming a category-defining platform in machine learning and artificial intelligence, everyone enjoys the upside.

We support the community. We believe major scientific advancements are the result of collaboration across the field. Join a community supporting the ML/AI community.