Spiral
Developer Relations Engineer
2d ago
175000 –275000 USD / yearUSAcontent creationtechnical writingbenchmarkingdata pipelinesgpu data loading
First Developer Relations hire responsible for creating content and developer experience materials to help researchers and engineers use Spiral's analytical database effectively.
Responsibilities
- This is our first DevRel hire, and it is a content and developer-experience role. You'll own the material that teaches researchers and training engineers how to get real work done with Spiral: cookbooks, worked examples, benchmarks, and reference pipelines grounded in datasets people actually train on. You might also conduct research on new applications of the core Spiral product.
- You'll collaborate with the rest of the team to create the tightest possible feedback loop between developers/researchers and our product and docs. The job is to earn credibility with a technical audience by shipping things that are genuinely good.
- Write technical cookbooks and end-to-end examples — video ingestion, GPU data loading for training, multimodal feature engineering — that a researcher can run and immediately understand.
- Build and maintain reference pipelines against real datasets (such as those on Hugging Face), and keep them working as the product moves.
- Produce credible benchmarks and the honest writeups that go with them.
- Be the developer's advocate internally: turn friction you and users hit into concrete product, client SDKs (e.g. pyspiral), and docs improvements.
- Answer real questions in the places our users already are (GitHub, community channels, conferences), and turn recurring ones into permanent docs.
- Represent Spiral at conferences.
- Give the occasional talk or workshop.
Requirements
- You've done ML or training-infrastructure work yourself, and you've personally felt the data-loading / video-decode / GPU-utilization pain we remove.
- You write well about technical things. You can point us to things you've written.
- You're fluent in Python and comfortable in the PyTorch / Hugging Face / data-pipeline ecosystem.
- You have a working mental model of GPUs, training loops, and where the bottlenecks actually are.
- You are well connected in developer and/or AI communities.
Nice to have
- Open-source contributions in relevant territory (PyTorch data / DataLoader, HF datasets, Ray Data, video/decode tooling, or similar).
- Experience with columnar / analytical data formats.
- An existing audience among ML practitioners — welcome, but genuinely secondary to the credibility above.
- Prior DevRel, AI research, or research-engineering experience.
Other
- Spiral builds a fast analytical database for multimodal, multi-rate data streams, on top of the open source Vortex file format. Our users are AI/ML researchers and AI infra engineers developing models in complex domains, such as weather & climate, financial, time-series, genomics, point-clouds, videos, and images. They spend their days waiting on data loaders, writing video or sensor data pipelines, and watching expensive GPUs sit idle on I/O. We make that pain go away.
- We're small, technical, and early. The way we win researchers & developers is by being useful to serious practitioners.
- Not a social-media-growth or "personal brand" role
- Not primarily events and evangelism
- Not marketing-with-a-little-code. This is engineering-grade technical work.