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Open nowPosted 58 days ago

AI Engineer — Learn Engine: Platform & Simulation

Hellyeah AI11 open roles

Where
San Francisco HQ
Work mode
On site
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Your applicationOpen nowAI Engineer — Learn Engine: Platform & SimulationHellyeah AI · San Francisco HQ

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The clock on this job

Early applications get read.

8.2% of postings close within 7 days. Measured by our own scanner across the market. Hellyeah AI postings stay open a median of 1 days.

Share of postings closed within
  1. 1.8%1 day
  2. 3.8%3 days
  3. 8.2%7 days
  4. 15.2%14 days
  5. 34.2%30 days
This job: posted 58 days ago

Hellyeah AI median: 1 days open

The posting

Build the tools that do not exist yet — a campaign simulator, a creative intelligence engine, an experimentation platform. This is invention work, not integration work. Every tool you build becomes a product moat that competitors cannot easily replicate. You will work alongside the intelligence engineer to create a closed-loop optimization system that gets smarter with every dollar spent.

Must Have: Has built platform/tooling systems that unlock new capabilities for users, not just internal plumbing.

- Strong TypeScript or Python with fast production shipping ability.

- Experience with browser automation, screen capture, simulation, or experimentation infrastructure.

- Strong product instincts for turning messy data and workflows into usable tools.

- AI-first development workflow with high implementation velocity.

Nice to have: Simulation engine / Monte Carlo / probabilistic modeling experience

- Computer vision or image analysis (for creative intelligence)

- Ad-tech or growth engineering background

- A/B testing or experimentation infrastructure experience

- Experience with Mastra, Langchain, or LLM orchestration frameworks

Own the platform and simulation layer of Learn Engine. Build the campaign simulator, experimentation infrastructure, screen-capture and creative-intelligence pipelines, and client-facing data products that let operators model outcomes before spending real money. This role owns tooling, infrastructure, simulation fidelity, and productized research surfaces — not the optimization policy itself.

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