About the job
About Chalk
Chalk is revolutionizing the data platform landscape, empowering the next generation of machine learning applications. By dismantling traditional barriers of complexity, latency, and scalability, we enhance the capabilities of ML. Our platform boasts Rust-speed performance combined with user-friendly tools that developers adore. Major corporations rely on Chalk for vital functions such as preventing fraudulent credit card transactions, identity verification, and optimizing clean energy utilization. Recently, we've raised a $50 million Series A round led by Felicis.
About the Role
In collaboration with our founders, you will spearhead a team of talented engineers dedicated to building our platform for real-time inference at scale. This position offers a unique chance to influence technical architecture and cultivate engineering culture in a rapidly-growing, early-stage company. You will work alongside exceptional individuals, including winners from Putnam and Advent of Code, former quants from Jane Street, and contributors to the Rust compiler—everyone committed to pushing the boundaries of what's achievable in ML inference.
We maintain a fully in-office work environment, five days a week. While we embrace flexibility for unavoidable conflicts, this role does not support hybrid work arrangements.
Your Responsibilities
- Lead a team of engineers focused on developing Chalk's data platform
- Collaborate with the founding team to define and implement our technical roadmap
- Establish engineering processes that promote high velocity while ensuring quality
- Engage directly with clients to understand their requirements and ensure that Chalk's platform effectively addresses real-world ML challenges
- Help shape Chalk's engineering culture as we expand—fostering top talent along the way
Qualifications
- A minimum of 5 years of engineering experience, including at least 2 years in a leadership role
- Prior experience in an early-stage startup environment
- Proven track record in building production-level ML systems or data infrastructure
- Exceptional programming skills and a strong understanding of systems architecture
- Proven ability to lead technical teams
- Excellent communication skills capable of bridging technical and business contexts

