Interpretable AI for drug discovery

Reticular helps pharma companies discover drugs with AI models like AlphaFold by making them steerable, just like you can prompt LLMs. Today, limited validation data means companies spend millions on failed experiments trying to steer these models through trial and error. We’re piloting our AI interpretability technology with early-stage biotechs and scaling rapidly. Just a week after our pivot, we identified the first interpretable features ever found in protein models, allowing precise control over biological functions. Nithin and John met competing in Biology Olympiads before spending 4 years as roommates at MIT publishing ML/bio research in NeurIPS and Nature. We believe biological models encode far more information than anyone is currently using - our goal is to unlock this potential.

ai-powered-drug-discoverygenerative-aibiotechtherapeutics

Total Open and Closed Positions

Total open positions, and positions newly closed since the previous update

Department Headcount Over Time

Open positions per department · top 6 at any point in the window

Newly Opened and Closed Positions

Position Churn Rate

Positions closed within 14 days of opening · a high rate suggests posting instability — duplicates, pulled listings, or roles filled through internal or off-market channels

Time-to-Fill Distribution

Days from open to close · closed positions only

Salary Trend Over Time

Monthly median base salary · USD · annualized · p25/p75 dashed

Salary Range by Department

Employment Type

Technical vs. Non-technical

Open positions · by department

Top Roles by Department

Seniority Mix

Derived from job title keywords

Equity Range by Department

Top Skills

Top Tech Stacks

Skills Trend

Change in share of postings · recent 3 months vs. prior 3 months

Tech Stack Evolution

Positions opened per month · top 5 technologies