Software Engineer II, Simulation
- Location
- US
- Workplace
- Remote
- Employment
- Full Time
- Salary
- USD 123,696–254,667/yr
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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