Design and build simulation environments that model CTV auction mechanics, inventory supply, and advertiser competition
Develop counterfactual and what-if frameworks for evaluating bidding strategies, budget allocation, and pacing algorithms offline
Build AI agents that explore strategy spaces, generate hypotheses, and automate experimentation within simulated environments
Use LLMs and generative AI to accelerate internal ML workflows — synthetic data generation, code generation, automated analysis, and rapid prototyping
Use simulation to de-risk ML model deployments — validate new bidding and optimization strategies before they touch live traffic
Define the technical direction for simulation and AI infrastructure and mentor engineers on the team

Strong production Python skills and experience building simulation or modeling systems
Deep understanding of probabilistic modeling, stochastic processes, or agent-based simulation
Hands-on experience with modern AI tools: LLMs, code generation, agentic workflows — and good judgment about when they help vs. when they don't
Adtech experience: you understand auction theory, RTB mechanics, and the dynamics of programmatic advertising
Ability to translate business questions ("what happens if we change our bid strategy?") into rigorous simulation frameworks
Clear written communication: you'll be defining new technical directions and need to bring others along
Ownership: you scope, design, and ship systems end-to-end with minimal direction
Nice-to-Haves:
Causal inference — uplift modeling, synthetic controls, difference-in-differences, or incrementality testing
Experience with discrete event simulation, Monte Carlo methods, or digital twins
Reinforcement learning — using simulated environments for policy learning and evaluation
Experience building agentic AI systems or multi-agent simulations
Big data experience with Scala and Spark
Systems programming experience in Zig or similar (C, C++, Rust)
MLOps experience — model deployment, monitoring, and pipeline orchestration on AWS

Machine Learning Engineer

Key skills