Developer Relations Engineer

Vast.ai•San Francisco, CA

2d•Onsite

About The Position

Vast.ai runs one of the largest GPU marketplaces in the world, with over 20,000 GPUs rented by more than 25,000 customers monthly for training, fine-tuning, and serving AI models. We are a profitable company with a flat team structure and rapid development cycles. This is an engineering role that operates in public, where you will be one of our heaviest users. A significant portion of your week will involve renting GPUs on Vast and building applications on them, such as serving open-source models with vLLM and SGLang, fine-tuning, running ComfyUI pipelines, and maintaining live inference endpoints. You will also be responsible for creating example repositories, Docker templates, and benchmarks for other developers. The remainder of your week will be dedicated to showcasing your work through short videos, technical write-ups, and engaging with the community on platforms like Discord and Reddit, as well as participating in hackathons. This role is not about building the Vast product itself, but rather about using it extensively in the open, identifying issues, and reporting back. If you are looking for a structured content calendar or a predefined campaign plan, this role may not be suitable. However, if you are someone who already experiments with GPUs on weekends to test new models, this role is for you.

Requirements

Can take an open source model from Hugging Face to a running endpoint on rented GPUs with nobody helping you.
Proficient in Linux, Docker, Python, SSH.
Can debug the GPU stack, including driver and CUDA mismatches, out-of-memory errors, and multi-GPU configuration (NCCL and topology issues).
Public proof of work shipped (GitHub profile, technical writing, or live projects).
Ability to work without a roadmap and prefer it that way.
Can explain a hard thing clearly, in writing and out loud.

Nice To Haves

Content or side projects that found a real audience.
Previous developer relations, community, or customer-facing work.
Experience with vLLM or SGLang internals.
Experience with distributed training (FSDP or DeepSpeed).
Experience with CUDA.
Experience working at a cloud, GPU, AI infrastructure, or developer tools company.

Responsibilities

Run real workloads on Vast every week.
Deploy, fine-tune, and serve open source models, and keep live endpoints running.
Build public example repos, Docker templates, and benchmarks that developers can clone and use.
Turn what you build into teaching: guides, short videos, talks, livestreams.
Be the most technically credible voice in our Discord, on Reddit, and on X.
Represent Vast at hackathons and conferences, roughly one trip a month.
Report the friction, the breakage, and the missing docs straight to engineering and product.