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Software Engineer

2 months ago
United States
Full-time
Lead
Software Engineer
Software Development
Apache Spark AWS C C++ LLM MLOps Python Reinforcement Learning Rust Scala Zig
Apply Now
tvScientific

tvScientific

tvScientific offers a pioneering Connected TV advertising and marketing platform that integrates traditional television's impact with the effectiveness of digital advertising, specifically tailored for performance marketers.

Media
11-50
Founded 2020
$22M raised
View All Jobs 15

Description

  • Design and build simulation environments that model CTV auction mechanics, inventory supply, and advertiser competition.
  • Develop counterfactual and what-if frameworks to evaluate 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 deployments by validating new bidding and optimization strategies before they reach live traffic.
  • Define the technical direction for simulation and AI infrastructure and mentor engineers on the team.
  • Translate business questions into rigorous simulation frameworks that can be used for analysis and decision-making.
  • Scope, design, and ship systems end-to-end with minimal direction.

Requirements

  • Systems programming experience in Zig or a similar language such as C, C++, or Rust.
  • Deep understanding of probabilistic modeling, stochastic processes, or agent-based simulation.
  • Hands-on experience with modern AI tools, including LLMs, code generation, and agentic workflows.
  • Adtech experience with understanding of RTB mechanics and programmatic advertising dynamics.
  • Ability to translate business questions into rigorous simulation frameworks.
  • Clear written communication skills for defining technical directions and aligning others.
  • Demonstrated ownership in scoping, designing, and shipping systems end-to-end with minimal direction.
  • Demonstrated ability to use AI to improve speed and quality in day-to-day workflow for relevant outputs.
  • Strong track record of critical evaluation and verification of AI-assisted work, including testing, source-checking, data validation, and peer review.
  • High integrity and accountability when handling sensitive data and final deliverables.
  • Strong production Python skills and experience building simulation or modeling systems are preferred.
  • Causal inference experience, such as uplift modeling, synthetic controls, difference-in-differences, or incrementality testing, is preferred.
  • Experience with discrete event simulation, Monte Carlo methods, or digital twins is preferred.
  • Reinforcement learning experience using simulated environments for policy learning and evaluation is preferred.
  • Experience building agentic AI systems or multi-agent simulations is preferred.
  • Big data experience with Scala and Spark is preferred.
  • MLOps experience with model deployment, monitoring, and pipeline orchestration on AWS is preferred.

Benefits

  • Base salary range of $123,696 to $254,667 USD for US-based applicants.
  • Eligible for equity.
  • Remote work indicated by #LI-REMOTE.
  • Relocation assistance is not available for this role.
  • Access to Pinterest culture and benefits, with details available on the company careers site.

Interested in this position?

Apply directly on the company website

Apply Now

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