Autonomous performance marketing

Advertising today is like trading in the 1980s pits: archaic, manual, and iterative guesswork. Humans update bids and keywords using noisy, delayed data with fixed rules that both break at scale and ignore stochasticity. We've built quantitative systems that advertise the way modern hedge-funds trade markets: continuous decision-making under stochastic outcomes and explicit profit constraints. We use customers' existing ad copy and use reinforcement learning and train our own LLMs to run ads on autopilot, harvesting profits when we’re confident and borrowing signals from similar keywords when data is sparse. Starting with brands on Amazon, we are automating tens of millions in live ad spend, increasing gross sales while decreasing advertising cost of sales by 40%.

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