Cloud ML DevRel Engineer - US remote
Company: Hugging Face
Location: New York (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-05-29
About this role
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. Yo...