Machine Learning Engineer

🚀 Machine Learning Engineer / Member of Technical Staff, ML & Optimization

📍 San Francisco

💰 $160K – $250K + equity

🏢 Confidential AI Startup

We’re partnering with an early-stage AI company building an AI Operator for growth, using ML, optimization and risk management to autonomously manage ad spend.

Think quant-style trading systems applied to digital advertising.

The company is already:

• Managing spend for global consumer brands

• Driving 20–50% efficiency improvements

• Backed by leading venture investors

• Targeting a Series A this year

• Scaling a small, highly technical founding team

This is a true end-to-end ML role. 

You’ll be working across:

• Value models for LTV and campaign performance

• Risk-aware budget allocation and optimization

• Creative fatigue and market inefficiency detection

• Execution-layer integrations with major ad platforms

• Production deployment, monitoring and model iteration

• Backtesting and simulation before capital is deployed

They’re looking for someone with:

• 4+ years of ML / optimization experience

• Strong production engineering skills

• Comfort with classical ML, regression, statistics and linear algebra

• A pragmatic, high-velocity approach to building

• Interest in quant-style systems, markets and automation

• Ability to own systems from research through production

Bonus points for:

• Convex optimization

• Quant finance or algorithmic trading

• Programmatic advertising / RTB

• Control theory

• AI-native engineering workflows

This is a high-ownership opportunity to build ML systems that make real decisions in live markets, not just models that sit in notebooks.

Message me to learn more.