Polymath
https://polymathlabs.aiSimulated worlds to train & evaluate long-horizon AI agents
We’re heading towards a future where AI agents will be able to perform useful work over long horizons, with little or no human supervision. To increase the reliability, performance, and safety of autonomous agents, they must be trained in simulation environments that reflect the real world. Polymath builds simulated worlds for agents to practice and learn through experience. We're a team of researchers and engineers from UC Berkeley, Hume AI, Plaid, and Amazon. We have years of experience post-training frontier models in industry, and building large scale data systems. Polymath is backed by Y Combinator.
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