Developer Relations Engineer
Indexed description
The role
This is an engineering role that happens in public — not a content-calendar job. You'll be Vast's resident power user: most of your week is spent renting GPUs on the platform and making them do impressive things — deploying and serving open-source models with vLLM, SGLang, PyTorch, and ComfyUI, keeping live endpoints running (including token endpoints on markets like OpenRouter), and building the example repos, templates, and benchmarks that show developers exactly how to do the same.
Then you teach it: short videos, technical guides, Discord and Reddit answers, hackathons. You won't be building the product — you'll be using it harder than any customer, in public, and feeding what breaks straight back to engineering.
What you'll do
- Run real workloads on Vast weekly: deploy, fine-tune, and serve open-source models; keep live inference endpoints up
- Build public example repos, Docker templates, and benchmarks; contribute to our open-source CLI/SDK and serverless tooling
- Turn what you build into teaching: guides, short videos, talks, livestreams
- Be the most technically credible voice in our Discord, Reddit, and X communities, and represent Vast at hackathons and conferences
- Close the loop: report the friction, breakage, and missing docs you hit directly to engineering and product
- You can take an open-source model from Hugging Face to a running endpoint on rented GPUs without hand-holding: Linux, Docker, Python, SSH
- You can debug the GPU stack: driver/CUDA mismatches, OOM errors, and multi-GPU config (NCCL, topology) don't scare you
- Public proof of shipped work: GitHub, technical writing, or live projects — we'll ask you to walk us through code you wrote
- Self-directed: no one here will hand you a roadmap, and you prefer it that way
- You can explain hard things clearly, in writing and in person
- Prior DevRel, community, or client-facing experience (a bonus here, not the job)
- vLLM or SGLang internals, distributed training (FSDP, DeepSpeed), CUDA
- Time at a cloud, GPU, AI-infrastructure, or developer-tools company
- Content or projects that found a real audience
- Ship several public example projects on Vast, including at least one live serving endpoint
- Publish benchmarks or guides developers actually use and share
- Become the recognizable technical voice in our community channels
- Represent Vast at a sponsored hackathon
Compensation Range: $160K - $200K
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