Senior Applied Scientist II, Ads Optimization
Core
Lead algorithmic direction for real-time bid optimization, budget pacing, and auction mechanics in Instacart's $1B+ ads business to maximize advertiser value and platform revenue.
Role type
Senior Applied Scientist II (Control Theory & Optimization)
Builds
Real-time bidding systems, budget pacing algorithms, and auction mechanics for grocery delivery ads.
Domain
Grocery delivery / Computational Advertising / Auction Economics
Deliverable
production ML models
Required skills
Constrained optimization, Control theory (PID, MPC), Auction theory and mechanism design, Dynamic programming, Go/Java/C++ for production, Python for data analysis
Preferred skills
Real-time bidding systems experience, Budget-constrained allocation methods, Causal inference and experimental design, Technical strategy shaping
Technologies
Go, Java, C++, Python
Responsibilities
Design real-time bid optimization systems translating advertiser goals into optimal auction bids; Build intelligent budget pacing algorithms distributing spend across time; Develop analytical frameworks connecting bidding, pacing, and budgeting; Shape auction mechanics including reserve pricing and multi-slot allocation; Own the full research-to-production loop from hypothesis to impact measurement.
Seniority
Senior, hands-on IC
