Machine Learning Engineer

🚨 Hiring: Machine Learning Engineer (Optimization / Decision Systems)

📍 San Francisco (Onsite)

💰 Up to $250K + Equity (Dependent on experience)

Most companies still manage digital advertising like it’s 2015. Manually adjusting budgets, guessing which campaigns work, and relying on black-box metrics from ad platforms.

We’re working with a venture-backed startup building something very different:

An AI-driven optimization engine that autonomously allocates advertising spend using the same quantitative rigor used in high-frequency trading and financial markets.

Instead of humans manually managing campaigns, their system continuously decides:

• Where budget should go

• When bids should change

• Which creative is losing performance

• How to maximize return across platforms

What You’ll Work On:

🧠 Build models for LTV prediction and budget optimization

⚙️ Design risk-aware algorithms that control how millions in ad spend is deployed

🔌 Build real-time integrations with platforms like Meta, Google & TikTok

📊 Develop simulation & backtesting systems before strategies go live

🚀 Take models from research → production → monitoring

Ideal Background:

✔️ 4+ years in Machine Learning or Applied ML Engineering

✔️ Strong foundation in statistics, probability, and optimization

✔️ Experience deploying ML models in production systems

✔️ Builders who care about real-world impact, not just research

⭐ Bonus if you’ve worked in quant finance, algorithmic trading, or adtech

Why This Role Is Interesting:

• You’ll build systems that control real-world financial decisions

• Early engineer helping shape the core architecture

• Opportunity to work on a $1T+ global market

• Meaningful equity at an early stage

If you're interested or know someone who might be, DM me or apply below 👇👇