Staff Machine Learning Manager

About the role

You're not waiting for data - you're building the intelligence layer on top of a live system The feedback loop between model and revenue is short The problem is genuinely hard : Cross-channel marketing optimization is a multi-objective, partially-observable, adversarial optimization problem. The ad platforms themselves are black boxes.

What you'll do

• Own the entire ML stack - from defining the roadmap to hiring the team to shipping models into production
• Architect and build the foundational ML capabilities that become the platform's core competitive moat: cross-channel intelligence that autonomously optimizes marketing…
• Report to the engineering leadership and work closely with product, data engineering, and the existing platform engineering team
• Build spend pacing algorithms that distribute budget optimally across time (dayparting, day-of-week, seasonality)
• Design incrementality testing frameworks to validate attribution models and feed insights back into budget allocation and bid optimization

What you need

• 8–14 years in data science & ai
• Machine learning
• LLMs
• Any graduate