Description review
VLM Run ( ) | 1x Founding Infrastructure Engineer
VLM Run ( ) · Remote · back to the listing
HR standards
36/100
poor
Title ↔ description
41/100
poor
Reads as
Unclear
no confident match
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
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Startups
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What the listing never says
- No section describes what the person would actually do. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
We’re building the inference platform for visual intelligence. We’re a deeply technical team of veteran AI / computer-vision engineers (
20+ years1
combined, MIT/CMU PhDs) who’ve shipped production ML infrastructure across autonomous driving and LLMs.
We just launched the VLM Run Gateway (https://vlm.run/gateway), a unified API that serves open-weight VLMs, embodied VLAs, ViTs, served across a fleet of GPUs and clouds. That's exactly the infrastructure problem this role will own.
If you’re interested, email us at [email protected] with your GitHub profile and link to projects you’ve recently built - especially with docker, k8s, GPUs.
We just launched the VLM Run Gateway (https://vlm.run/gateway), a unified API that serves open-weight VLMs, embodied VLAs, ViTs, served across a fleet of GPUs and clouds. That's exactly the infrastructure problem this role will own.
If you’re interested, email us at [email protected] with your GitHub profile and link to projects you’ve recently built - especially with docker, k8s, GPUs.