iollo | San Francisco/Remote (US) | Full-time
Compensation: $170K–$250K + equity
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iollo is Stanford-founded and Y Combinator-backed. We’ve built Quinn, an AI scientist that compresses months of pharma R&D into days for top-tier partners.
The role: deliver Quinn’s science directly to pharma R&D teams and ship what you learn back into the product.
What you’ll do
• Work alongside Quinn to deliver for pharma partners and present findings to their R&D leadership
• Run Quinn and own the quality of what ships
• Write and evaluate LLM prompts
• Ship what you learn back into Quinn to extend its capabilities
You may be a good fit if you have
• A PhD in a life sciences discipline (biology, chemistry, pharmacology, or related) with computational fluency
• 3+ years in pharma R&D with exposure to multiple stages — not just one silo
• Delivered scientific findings directly to R&D leadership or external partners
• Shipped tools, pipelines, or outputs that other people actually used for decisions
• Hands-on comfort with Git, Python, LLM workflows, and prompt/eval loops
• A self-directed approach — you figure out what needs to happen and do it
You’ll stand out if you
• Understand drug development from target to clinic, not just your specialty
• Built something real with LLMs and can explain what worked and what didn’t
• Have written decision memos, not just papers
You might be exactly right if you’re one of these
• An ex-biotech computational scientist who became a product person or operator
• A scientific AI product engineer — hands-on with LLM workflows, thinks in product outcomes
• A technical PM from scientific software who uses the tools and inspects outputs directly
You’d be Quinn’s scientific voice at the partner table. Quinn finds things human teams miss — you make the call and deliver to partners in days, not quarters. If you want to define how AI gets used in drug discovery, let’s talk.