# AI Engineer — Learn Engine: Platform & Simulation at Hellyeah

> Onsite · United States · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/ashby%3Ahellyeah%3A9c0cc578-9d91-4b30-8c8e-863f82d27734 (read 2026-11-08).

## Facts (observed)

- Company: [Hellyeah](https://alderhq.app/companies/hellyeah)
- Location text: San Francisco HQ
- Where it can be done from (inferred): Onsite · United States (evidence: "Location: San Francisco HQ")
- Posted: 2026-08-12 (88 days ago)
- First seen by alder: 2026-11-04 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/hellyeah/9c0cc578-9d91-4b30-8c8e-863f82d27734
- Skills listed (inferred): TypeScript, Python, LLMs

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (SF Bay Area, n 461): p25 $200k, median $250k, p75 $300k

## Description (the employer's text)

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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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Ahellyeah%3A9c0cc578-9d91-4b30-8c8e-863f82d27734 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.