Chalk Series A

Forward Deployed Engineer

San Francisco, CA On-site Added Jun 30

About the role

About Chalk Chalk is building the data platform that powers the future of machine learning applications. We tear down complexity, latency, and scale barriers that have traditionally constrained ML capabilities. Our platform combines Rust-speed performance with elegant tools that developers love to use. Leading companies depend on Chalk for everything from stopping fraudulent credit card swipes, verifying identities, and maximizing clean energy capture. We've recently raised a $50 million Series A https://www.reuters.com/business/databricks-competitor-chalk-raises-50-million-series-2025-05-28/, led by Felicis. About the role You are an exceptional software engineer who is able to build bespoke technical solutions and partner with machine learning teams to develop Chalk’s proprietary infrastructure. You will work with customers of Chalk to build efficient feature pipelines for problems in healthcare, finance, and recommendation systems. This role will give you a unique opportunity to work closely with customers, gathering requirements and engineering feature pipelines that support use-cases like cancer detection, fraud prevention, and product recommendation. This is your opportunity to join us in-person as an early employee and make a significant impact at a high growth start-up.  We're in the office 5 days a week. When unavoidable conflicts come up, we’re flexible. This is not a hybrid role. What you will do - Write code to implement Chalk technology for Chalk customers and prospects.

Industry

AI Infrastructure / ML Feature Store

Top skills for this role

  • Real-time ML feature pipeline engineering
  • 2. Customer-facing production ML deployment
  • 3. Healthcare/fintech domain knowledge

Languages

Python

Frameworks & tools

Python-native feature pipelinesSQLreal-time data systems

AI / ML skills

ML feature engineeringreal-time inferencedata pipelines

Customer skills

Enterprise ML deployment,partnering with ML teams on production feature pipelines

Domain knowledge

Healthcare AI,fintech,recommendation systems,MLOps

Travel: not specified
Equity: yes

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