Hellyeah
AI Engineer — Learn Engine: Intelligence & Optimization
- Confirmed live in the last 24 hours
- $200k–$1000k
- Mid level
- Full-time
- Remote · San Francisco HQ
- Added 1 month ago
About this role
This AI Engineer role focuses on building the intelligence layer for an autonomous growth operating system, automating campaign optimization and managing significant ad spend. You'll be responsible for developing recommendation engines and closed-loop decision systems that learn from campaign outcomes to continuously improve strategy. The position prioritizes decision quality and learning loops, rather than underlying platform infrastructure.
What you'll do
- Build recommendation engines for bid changes and budget reallocation.
- Develop closed-loop decision systems using campaign data.
- Define how the system learns and improves campaign strategy.
- Own the intelligence and optimization layer of Learn Engine.
- Design optimization policies and scoring systems.
- Ensure decision quality and optimization policy
What they're looking for
- Recommendation Systems
- Optimization
- Statistical Reasoning
- LLM Orchestration
- Experimentation
- AI-First Development
- Reinforcement Learning (plus)
- Hyperparameter Optimization (plus)
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Hellyeah
- Industry
- Technology & Software
Likely interview questions
- Describe a time you built a recommendation or optimization system that significantly improved future inputs.
- How do you approach experimentation and decision-making with noisy real-world data?