tvScientific
tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.
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 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
Systems programming experience in Zig or similar (C, C++, Rust)
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 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
Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.
Nice-to-Haves:
Strong production Python skills and experience building simulation or modeling systems
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
MLOps experience — model deployment, monitoring, and pipeline orchestration on AWS
At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
US based applicants only: $123,696 — $254,667 USD.
