About the job
About Chalk
Chalk is at the forefront of revolutionizing the data platform that drives the next generation of machine learning applications. We simplify the complexities of latency and scalability that have historically limited machine learning capabilities. Our platform integrates Rust-speed performance with user-friendly tools that developers love to utilize. Renowned companies rely on Chalk for diverse applications ranging from thwarting fraudulent credit card transactions to identity verification and optimizing clean energy utilization. Recently, we secured a $50 million Series A funding round, spearheaded by Felicis.
About the Role
As a talented software engineer, you will design tailored technical solutions and collaborate with our machine learning teams to enhance Chalk's proprietary infrastructure. You will engage with Chalk's clients to create efficient feature pipelines addressing challenges in healthcare, finance, and recommendation systems. This role presents a unique chance to work directly with customers, understanding their needs and engineering feature pipelines that support vital use cases such as cancer detection, fraud prevention, and product recommendations. Join us in-person as an early team member and make a significant impact at a rapidly growing startup.
We maintain an in-office presence five days a week, with flexibility for unavoidable conflicts. This is not a hybrid position.
Your Responsibilities
Develop code to implement Chalk technology for our clients. You will gain in-depth knowledge of Chalk's infrastructure and determine optimal integration methods across various environments.
Collaborate closely with our Engineering and Sales teams.
Serve as the principal technical contact during pre-sales and post-sales phases (including customer onboarding and support).
Advise clients on new product offerings as their businesses evolve.
Assist in interviewing and expanding the Engineering team.
Qualifications
A strong technical background with experience in software development or building machine learning models.
A minimum of 2 years of professional experience in backend software engineering.
Proficiency in Python and SQL.
Excellent collaboration and communication skills to work effectively in a team environment.

