🚀 ML Engineer — Decision Systems | San Francisco
Please note: Visa sponsorship is not available. Applicants must already be authorised to work in the US. US Citizens only.
What if your ML system didn’t just make predictions — it decided what happened next?
We’re hiring an ML Engineer to own the intelligence layer behind an autonomous growth platform. You’ll build the decision engine that determines how real advertising budgets are allocated, optimized, scaled, or paused — with every decision measured against actual returns.
This is production ML with real consequences, not a research sandbox.
We’re looking for:
- 3+ years shipping production ML or optimization systems
- Experience building closed-loop decision systems
- Strong statistical reasoning and experiment design skills
- STEM degree in CS, Math, Statistics, Physics, Engineering, or similar
- Someone who’s constantly experimenting with new ideas and technology
You’ll:
- Build recommendation & scoring systems for bids, budgets, and campaign actions
- Design closed-loop learning systems that improve from real-world outcomes
- Develop optimization policies, from rules to post-training and RL
- Orchestrate multiple AI agents and evaluate their decisions
- Own decision quality + ROI — not platform plumbing
Stack: Python · Machine Learning · Recommendation Systems · Reinforcement Learning · Ad Optimization · Bid Management
📩 Apply now or message me for a confidential conversation.