Hellyeah AI
AI Engineer — Learn Engine: Intelligence & Optimization
$200K
San Francisco HQ +1 · Hybrid · Full-time · Posted Aug 12, 2026
- Location
- San Francisco HQ
Shanghai
About the job
Own the intelligence and optimization layer of Learn Engine, building systems that recommend and automate campaign decisions and improve from outcomes over time.
What you'll do
- Build recommendation engines for bid changes, budget reallocation, pause/boost decisions, and postback optimization.
- Convert campaign data into optimization guidance and closed-loop decision systems.
- Define how the system learns from outcomes and improves campaign strategy.
What they ask for
- Experience building recommendation, optimization, or decision systems whose outputs improve future inputs.
- Strong statistical reasoning and experimentation judgment with noisy real-world data.
- Strong LLM orchestration or agent-system experience for reasoning over campaign context.
- Ability to design optimization policies, scoring systems, or automated recommendation loops and ship production systems quickly.
Nice to have
- Ad-tech optimization patterns, reinforcement learning, hyperparameter optimization, or model fine-tuning experience.
- Experience with agent-driven automation, Mastra or similar frameworks, or growth engineering, performance marketing, or data science.
Pay
$200K – $1M (currency not stated; compensation type not stated); 0.5% – 3% (equity type not stated)
Tools
LLM, Mastra, RL, HPO
AI focus
Build LLM- and agent-based campaign decision systems, optimization policies, and learning loops that improve from outcomes.
Model-written summary · the original posting is authoritative