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Hellyeah AI

engineering opportunity

AI Engineer — Learn Engine: Intelligence & Optimization

You will own the intelligence and optimization layer of the Learn Engine by building recommendation systems for ad spend and campaign strategy. Your work involves creating closed-loop decision systems that turn campaign data into actionable guidance to continuously improve performance.

San Francisco, California, United StatesremoteFULL_TIME

Posted

About the role

What will you do at Hellyeah AI?

Build the brain of an autonomous growth OS. The system you create will manage millions in ad spend and get measurably smarter with every dollar. This is the moat — every competitor has humans optimizing campaigns manually.

You are building the intelligence layer that compounds. The Platform engineer creates the tools, you create the decisions. Together you build something nobody else has.

Must Have:

Has built recommendation, optimization, or decision systems where outputs improve future inputs.

Strong statistical reasoning and experimentation judgment under noisy real-world data.

Strong LLM orchestration or agent-system experience for reasoning over campaign context.

Can design optimization policies, scoring systems, or automated recommendation loops.

AI-first development workflow and ability to ship production systems quickly.

Nice to Have

  • Ad-tech optimization patterns (bid management, budget allocation, ROAS optimization)
  • Reinforcement learning (RL) experience is a plus
  • Hyperparameter optimization (HPO) experience is a plus
  • Model fine-tuning experience is a plus
  • Experience building agent-driven automation (LLM agents that take actions)
  • Background in growth engineering, performance marketing, or data science
  • Experience with Mastra or similar agent orchestration framework
  • Own the intelligence and optimization layer of Learn Engine.
  • Build recommendation engines for bid changes, budget reallocation, pause/boost decisions, and postback optimization.
  • Turn SSOT campaign data into high-quality optimization guidance and closed-loop decision systems.
  • Define how the system learns from outcomes and continuously improves campaign strategy over time.
  • This role owns decision quality, optimization policy, and learning loops — not platform plumbing or simulator infrastructure.

Which skills does this role require?

AI EngineeringRecommendation SystemsStatistical ReasoningLLM OrchestrationAgent-system DesignAI EngineerAutonomous Growth OSOptimization PoliciesScoring SystemsProduction SystemsArtificial IntelligenceLLMsA/B Testing

Make your next move

Build a shortlist and prepare

Identify the requirements you can demonstrate, then choose examples from your work to discuss with the hiring team.

Review the responsibilities and requirements before adding an opening to your shortlist.

Role information can change. Confirm current details on the original application page.

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