AI Engineer

Job description

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](https://www.linkedin.com/in/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](https://www.linkedin.com/in/nateps/) 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 an elite team, with $125M in funding from top investors (Redpoint, First Round Capital, CRV, Conviction, Y Combinator) and leaders in healthcare and AI. This is a rare chance to join an early-stage 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 - Prompt optimization, red-teaming, and improving robustness of LLMs for life-science NLP applications within Collate’s products. - Build pipelines and infrastructure to deploy AI systems reliably, safely, and at scale. - Collaborate with product, design, and engineering teams to translate user needs into AI-driven features. - Develop evaluation frameworks to ensure models are accurate, fair, and trustworthy in real-world life science settings. - Experiment rapidly, while balancing iteration speed with the rigor required for high-stakes applications. - Create tools and workflows that make AI development more efficient across the team. ### What We’re Looking For - Hands-on experience building and deploying ML/AI systems in production. - Strong foundation in deploying search and retrieval systems and NLP applications. - Ability to bridge research and engineering — from prototyping models to shipping them in user-facing products. - Comfort working in an early-stage startup where ambiguity is high and ownership is expected. - Motivation to apply AI to life sciences in a way that prioritizes reliability, safety, and impact.