Hugging Face

Cloud ML DevRel Engineer - US remote

🇺🇸 Remote, United States Remote IT Full time Senior Posted May 29, 2026
Location Remote, United States
Workplace Remote
Employment Full time
Seniority Senior
Category IT
IT Category Data Science & ML
Language English
Posted May 29, 2026
Last verified May 29, 2026
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Role summary by JobGrid

Cloud ML DevRel Engineer - US remote at Hugging Face is a Senior, full-time IT/Data Science & ML role in Remote, United States. JobGrid adds normalized role facts, comparable classification, source freshness, and the original public application path while keeping original-language boundaries intact. This listing is part of JobGrid's Remote AI jobs from public company career pages.

  • Remote, United States; full-time; Senior; category IT, subcategory Data Science & ML.
  • Source posted 2026-05-29 and last checked 2026-05-29, so the page can show recent source timing.
  • No salary is listed in the payload, so JobGrid does not add salary context here.
  • Candidates are sent to the original public application page with non-personal referral parameters.

At Hugging Face, we're on a journey to democratize good AI. We're building the fastest-growing platform for AI builders, with over 11 million users who have shared more than 2M models, 700k datasets, and 600k apps. Our open-source libraries have more than 600k stars on GitHub.

About the Role

As a Cloud ML DevRel Engineer, your goal is to grow the impact of the Hugging Face ML Cloud team by teaching the community of ML practitioners how to accelerate their training and inference workloads.

The ML Cloud team works through strategic collaborations with the most widely used clouds (AWS, GCP, Azure, Cloudflare), AI accelerators (NVIDIA, AMD, Intel Gaudi, AWS Inferentia, TPU), and systems partners (Dell, Nutanix), to make it easy for the community to run Hugging Face models and libraries on these platforms. These partnerships sit at the core of our strategy as an open platform with no customer lock-in, and of how we drive usage and revenue for our partners.

This is a solid engineering role with a strong flavor of education and community. Your impact comes from driving visibility and usage of partner integrations, through work like:

  • Publishing technical blog posts
  • Contributing documentation and code examples
  • Speaking to business and technical audiences at partner conferences
  • Producing and running webinars
  • Building and showing off demos
  • Leading go-to-market conversations with strategic partners

You'll work at the front edge of generative AI and open source, hand in hand with some of the most important companies in the field. You'll have a lot of autonomy and full creative control, with the goal of having 10x the impact of a similar role at a big tech company.

About You

You're already an active voice in the ML community. You publish, you teach, and people follow your work on LinkedIn and X.

You care about ML engineering, building practical AI applications, shipping them to production, and squeezing the most out of the cloud to accelerate them. You like learning hard engineering concepts and talking them through with other engineers, and you take pride in code that's easy to read. You're a strong communicator and educator, and you enjoy engaging with the ML community in a positive, helpful way.

What you'll need

  • 3+ years in developer relations or developer advocacy, specifically for ML or AI products, tools, or platforms
  • An established public presence as a technical voice, with a track record of regularly publishing ML/AI content and a demonstrable, engaged audience on LinkedIn and X (Twitter)
  • A portfolio of developer-facing content you can point to: technical blog posts, conference talks, demos, code examples, or documentation
  • Comfort and experience with public speaking to technical audiences (conferences, webinars, workshops)
  • 3+ years of hands-on ML or software engineering experience, including taking models to production
  • Experience training or deploying ML models on at least one major cloud (AWS, GCP, or Azure)
  • Proficiency in Python
  • Practical experience with the Hugging Face stack (Transformers, the Hub, Inference Endpoints) or comparable open-source ML libraries
  • Working knowledge of GPUs or AI accelerators (NVIDIA, AMD, Intel Gaudi, AWS Inferentia, or TPU) and of training and inference optimization
  • Fluent written and spoken English

Nice to have

  • Open-source maintainer or contributor experience
  • An active presence in other developer communities (GitHub, Reddit, YouTube, Discord)
  • Familiarity with containers and orchestration (Docker, Kubernetes)
  • Experience with distributed training or inference-serving frameworks (for example vLLM, TGI, or Ray)

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”. No trick, no catch, it just tells us a real person is on the other side. 🤗

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.