At Verda, we're building a vertically-integrated European cloud computing platform designed for the full ML model lifecycle. Our growth depends on AI engineers and researchers finding Verda through technical content they trust and that respects their time - benchmarks they can reproduce and walkthroughs that get them to a result. That work has to come from one of them.
Join Verda while it's still being built - not once it's finished!
Why Verda
Verda is at the frontier of ML systems and AI infrastructure. As NVIDIA Preferred Partner, we've consistently been among the first to deploy across every hardware generation - from Ampere to Blackwell. Our customers include 1X, SGLang, and vLLM, and we've collaborated on ecosystem engagements with PyTorch, SemiAnalysis, and GPU MODE. Our internal AI Lab conducts research into ML systems engineering and model x hardware co-design, spanning distributed training, post-training RL, inference at scale, compilation, and kernels.
About the role
You will be Verda's public technical voice for AI engineers and researchers. You will create deep-dive articles, benchmarks, walkthroughs, tutorials, and demos covering the ML model lifecycle - and build reproducible technical assets (repos, deployment templates, integrations) that AI developers can clone, run, and adapt to their own work.
You will represent Verda at community meetups and industry events - speaking, running workshops, and engaging directly with engineers and researchers where they already are. You will collaborate with the world's leading AI companies across our partner network on co-authored content and technical deep dives that expand Verda's credibility in the broader AI ecosystem.
You will work closely with our internal AI Lab as well as product engineering and go-to-market teams to identify high-impact ML/AI topics, translate new platform capabilities into developer-focused work, and feed the editorial calendar with material AI developers actually want to read.
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