AI Research Scientist

Job Description

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 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 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 Research Scientist to push the boundaries of how advanced AI can be applied in healthcare. You’ll explore new modeling approaches, design novel architectures, and prototype capabilities that don’t exist yet — always with an eye toward how they can be translated into safe, reliable, and impactful products.

This is not a pure research role. At Collate, research is directly tied to deployment. You’ll work side by side with engineers, product, and Life science  experts to ensure that breakthroughs in the lab become real solutions in the world.

What You’ll Do

• What You’ll DoExplore new LLM prompt optimization, robustness of LLM applications and modeling approaches in machine learning, NLP, and reasoning.
• Prototype and validate AI capabilities that expand Collate’s product roadmap.
• Collaborate with engineering, product, and design to bring research into production.
• Develop evaluation frameworks to measure safety, reliability, and fairness.
• Share findings with the broader AI community through publications and open collaboration.
• Help shape the long-term research agenda at Collate.

What We’re Looking For

• Strong background in machine learning, NLP, or related fields, with publications or equivalent experience.
• Ability to balance theoretical complexity and simplicity of maintaining and improving real world AI applications in life science. 
• Experience troubleshooting NLP performance gaps and improving applications using online and offline evaluation.
• Experience in translation is an added bonus
• Hands-on experience building and experimenting with deep learning models (e.g., PyTorch, JAX, TensorFlow).
• Ability to bridge theory and practice — from new research ideas to real-world deployments.
• Curiosity-driven, with a track record of pushing beyond the obvious to uncover new possibilities.
• Motivation to apply AI research in Life sciences , where rigor, safety, and impact matter deeply.
• Excitement to work in an early-stage environment where you help define not just the research, but the product and company direction.

Why Join Collate?

Impact: Build systems and experiences that touch real patients and providers, improving healthcare outcomes.

Ownership: Shape both our product experience and our engineering culture from the start.

Learning: Collaborate with a uniquely interdisciplinary team—AI researchers, healthcare leaders, and experienced startup builders.

Upside: Join a company early enough to have meaningful equity and career-defining impact.

The base salary range for this role is depending on experience and level (Tier 1, San Francisco)

Research Scientist: $188-215K; Senior Research Scientist: $188-275K; Staff Research Scientist: $228-310K; Principal Research Scientist: $275-350K

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.