Chalk builds a feature store and data platform for ML teams, emphasizing sub-second latency and on-demand compute across AWS and GCP. The tech stack spans Rust, Python, Go, and TypeScript—a polyglot, systems-heavy foundation suited to performance-critical infrastructure. The hiring mix is balanced between engineering and sales (16 roles each), with decelerating velocity; active projects reveal a sales and go-to-market maturation phase (account management, customer health scoring, pipeline creation) alongside core product exposure to data scientists, suggesting a transition from product-market fit toward operational scaling.
Tech Stack 15 technologies
What Chalk Is Building
◆Challenges
- Complexity, latency, and scale barriers
- Dbms query planning & optimization
- Fraudulent credit card swipes
- Maximizing clean energy capture
- Distributed analytical data processing systems
- Building diverse talent pipeline
- Scaling technical organization
- Scaling post-sale motions
- Increasing pipeline and revenue
- Optimizing outreach effectiveness
▲Active Projects
- Feature pipelines for product recommendation
- Build account management function
- Design customer health scoring
- Productionize first iteration
- Multi-touch attribution framework
- Outreach campaigns for pipeline creation
- Expose core platform to data scientists
- Build scalable approach to customer wins
- Design and execute multi-channel sourcing strategy
- Build scalable recruiting process
Hiring Activity
65 roles · 9 in 30d
Department
Seniority
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