AI Engineer
San FranciscoRemoteFull-time
AI Summary
AI Engineer at Collate builds and productionizes models powering life-science AI features, bridging research and software to deliver reliable, user-facing capabilities.
About this role
About Collate
Collate is an AI document generation platform for life sciences. We automate paperwork with AI, helping our customers get life-saving innovations to patients years faster. Collate is an end-to-end solution, powering every step of drug, diagnostic, and medical device development—from concept to market.
Our CEO Surbhi Sarna is a former General Partner at Y Combinator. Surbhi founded nVision Medical, which developed a new method to detect ovarian cancer and was acquired by Boston Scientific. Our CTO Nate Smith is a former Visiting Partner at Y Combinator and founder of Lever. Our AI researchers, engineers, and designers have worked at Google, Nvidia, Meta, Netflix, Amazon, AirBnB, Hippocratic AI, and Grail, and 40% of our team are former founders.
We’re a small, elite team, with over $30M in seed funding from top investors (Redpoint, First Round Capital, Conviction, and Y Combinator) and leaders in healthcare and AI. This is a rare chance to join at the ground floor of a company with world-changing potential, experienced founders, and resources to execute at scale.
About the Role
We’re looking for an AI Engineer to help build and productionize the models and systems that power Collate’s products. You’ll work at the intersection of machine learning, software engineering, and product — turning cutting-edge research into reliable, user-facing capabilities.
This is an opportunity to shape how advanced AI is applied in Life sciences — a space where performance, safety, and trust matter as much as innovation. As one of the first AI-focused engineers at Collate, you’ll define the standards for how we evaluate, and deploy models that directly impact drug and medical device development.
What You’ll Do
What We’re Looking For
Skills
Cross-Functional CollaborationCustomer-facing AI FeaturesData PipelinesExperiment DesignFairness And Trust In AIInfrastructure For AI SystemsLLM RobustnessML/AI System DeploymentMLOpsModel Evaluation FrameworksNLPProduction PipelinesPrompt EngineeringPrototyping To Shipping ModelsRed TeamingRisk Assessment In Life SciencesSafety And Reliability In AIScaling ML SystemsSearch And Retrieval SystemsTooling For AI Development
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