JobHabor

Software Engineer II, Simulation

Pinterest

Location
US
Workplace
Remote
Employment
Full Time
Salary
USD 123,696–254,667/yr
Apply on the employer’s site

Posted 2mo ago

The employer’s full description could not be read from their board. This is a summary of the posting — follow the apply link for the original.

Responsibilities

  • 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
  • Define the technical direction for simulation and AI infrastructure
  • Mentor engineers on the team

Requirements

  • 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
  • Adtech experience: you understand RTB mechanics, and the dynamics of programmatic advertising
  • Ability to translate business questions into rigorous simulation frameworks
  • Clear written communication
  • 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
  • Strong track record of critical evaluation and verification of AI-assisted work
  • High integrity and ownership
  • Bachelor’s degree in computer science, machine learning, statistics, a related field or equivalent experience

Preferred

  • 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

Skills

  • Zig
  • C
  • C++
  • Rust
  • LLMs
  • Python
  • Scala
  • Spark
  • AWS

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