Senior Staff Machine Learning Engineer, Ads Ranking

Role overview

This is a senior staff-level machine learning engineering role on an ads ranking team, focused on applying agentic AI to reshape how ML models are designed, trained, and evaluated. The work centers on modeling leverage—improving model quality and velocity rather than building general-purpose infrastructure—and requires operating as a technical leader across the full modeling loop. It suits someone who combines deep ML fundamentals with hands-on fluency in AI-assisted development systems.

Responsibilities

- Design and ship advanced ML models alongside agentic workflows that help teams iterate on data, features, architectures, hyperparameters, and error analysis. - Use AI-assisted development tools (for example, large language model coding assistants and comparable systems) to investigate model behavior, generate and test hypotheses, automate repetitive analysis, and tighten experiment quality. - Build reliable evaluation harnesses covering correctness, reproducibility, regressions, cost, latency, and overall agent or workflow quality. - Run architecture comparisons and rigorous experiment readouts, turning findings into clear recommendations for the broader team. - Partner with product, data science, ML infrastructure, and engineering stakeholders to connect modeling improvements to user and business outcomes. - Set technical direction across teams, mentor engineers, and raise the bar for modeling rigor and AI-assisted engineering practices.

Requirements

- 9 or more years of experience in ML engineering, applied ML, or a closely related field, with substantial production impact. - Demonstrated senior staff-level technical leadership, including a track record of influencing modeling direction across multiple teams. - Deep expertise across the modeling stack: data, objectives, architectures, optimization, evaluation, and experimentation. - Concrete examples of using agentic AI or AI coding tools in a way that improved ML outcomes, not just coding speed. - Ability to design guardrails and evaluations that make autonomous or semi-autonomous workflows trustworthy. - Strong Python skills and fluency with modern ML frameworks and data tooling, plus clear, concise communication and a collaborative, low-ego leadership style.

Benefits and work setup

- 100% remote within the US, with optional hybrid or onsite work at offices in New York, San Francisco, Los Angeles, and Chicago. - Base salary range of $292,500 to $409,500 USD, plus equity in the form of restricted stock units. - Comprehensive medical, dental, and vision coverage, a home office setup stipend, and generous 401(k) matching. - Flexible vacation policy, four or more months of paid parental leave, family planning support, and paid volunteer time off.