Chalk

another hiring post. looking to build out a few teams across Chalk's GTM org - coast to coast. as always looking to add incredible SDRs to Chris Studley's powerhouse team. LA and SF office only. too much pipeline is always a good problem to have. opening up additional AE HC across NY/LA/SF to help keep up with the world-class growth marketing and outbound is driving. and lastly, here at chalk, we know content is king. looking to add another developer advocate/evangelist. looking for a die-hard creative comfortable across many channels (video, social, longform, community, IRL etc). help us bring the look and feel of chalk's ergonomics to the wider dev community. as always feel free to DM me or apply directly below (we do look at every application :)

The SF office pedaled through their power cycling class! Turns out we spin up more than just sandboxes. 🚴

"We can develop a new recommendation algorithm in the span of a few days." Whatnot on how Chalk turned speed into scale — and what that unlocked for fraud detection, discovery systems, and beyond.

Welcome Elizabeth Gomes to the Chalk NY team as our Office Manager! 🗽 Elizabeth — who goes by Monica — joins us from New Jersey (proud Rutgers grad!) with a background in hospital administration and hospitality, so she's more than ready for the fast-paced startup life. When she's not keeping the office running smoothly, you'll find her deep in sci-fi and dystopian fiction like many of us at Chalk. Welcome to Chalk, Monica! 👋

"With Chalk, our iteration speed went from days to hours." Verisoul protects fintech, gaming, and SaaS platforms from fake account attacks. But their old infrastructure turned every update into a multi-day project, limiting how quickly they could respond to new attack patterns. They transformed their detection system with Chalk: ⬆️ 10x faster model deployment 🎯 4x more accurate decisions with real-time data 📒 Full auditability — instant explanations for every fraud flag Full story in comments!

Proud of the Chalk team and what they're building. 🥳

🚀 Big congratulations to Runway and Chalk for being named on the Foundational AI: The 8 Next Big Things in Tech 2025 by Fast Company! Runway is carving new paths in AI-powered video, tackling one of the trickiest frontiers: maintaining consistency across characters, objects, and scenery across multiple clips. Their Gen-4 model is a leap toward making AI video production viable for film, gaming, advertising, virtual try-ons, interior design, and more. Chalk is paving the way for AI infrastructure to feel less like plumbing and more like a seamless foundation. Their end-to-end platform lets developers focus on building, not wiring things together. At Felicis, we believe in backing companies that are pushing the boundaries of what's possible with AI. And tackling foundational challenges like infrastructure, consistency, scale are just as critical as headline-grabbing use cases. https://lnkd.in/gk7NCrqK

We had to rack bare metal to compile our software because peoples’ laptops were melting. Chalk compiles a lot of code and our laptops just couldn't keep up with the build times. Instead of paying AWS for slow cloud instances, we bought our own hardware. It sits by our lunch table in our NY and SF offices. The fastest CPU you can buy on Newegg is straight-line faster than anything available on AWS. For compilation workloads, you don't need horizontal scaling - you need raw single-threaded performance. Sometimes the right answer is just buying better metal.

Thrilled to welcome Sheridan L as Chalk's newest Frontend Engineer! Sheridan joins us with a passion for building intuitive, user-friendly UIs that make a real impact. When not crafting beautiful interfaces, you'll find him staying competitive both indoors (Dota 2 ⚔️) and outdoors (pickleball 🏓). Welcome aboard, Sheridan!

Does your feature DAG look like a conspiracy theory board? 🕸️ It's the curse of sophisticated ML models: thousands of interdependent features creating duplicate transforms and cascading failures. Fintech Mission Lane has tamed this beast. They use Chalk to iterate on massive DAGs interactively while maintaining reliable lineage at scale. Join us on October 28th at 11am PT for a live demo where Michael Kuhlen will show how they: ▪ Modify complex feature graphs without breaking downstream dependencies ▪ Reuse derived features across teams instead of recomputing everywhere Luma link in comments!