Director, Machine Learning Engineering, Ads Measurement (AI)

Location: Hybrid role based in San Francisco, Palo Alto, or Seattle, United States. Relocation assistance is not available.

Company

hirify.global is a visual discovery platform helping people find creative ideas, plan projects, and create lives they love.

What you will do

• Define technical strategy and investment priorities across Interfaces, Ingestion, User Match, and Conversion Quality.
• Lead managers and senior technical leaders across multi-year machine learning and data-platform investments.
• Translate advertiser and business challenges into scalable machine learning, data, and platform solutions.
• Improve experimentation, causal measurement, model quality, reliability, privacy, and production operations.
• Establish cross-team design reviews, shared metrics, dependency management, and launch governance.
• Recruit, retain, and develop a high-performing, inclusive engineering organization while communicating strategy and outcomes to executives and cross-functional partners.

Requirements

• Strong background in ads measurement, identity, signals, and large-scale data processing.
• Experience leading engineering organizations through managers and senior technical leaders.
• Ability to define and execute technical strategy across multiple teams.
• Experience operating systems with demanding scale, reliability, privacy, and data-quality requirements.
• Strong executive communication, analytical thinking, and cross-functional influence.
• Bachelor’s degree in computer science, statistics, machine learning, or a related field, or equivalent experience.

Nice to have

• Experience leading through privacy, browser, platform, or signal-availability changes.
• Experience with ads optimization, privacy-enhancing technologies, probabilistic matching, graph systems, anomaly detection, event-quality modeling, or confidence scoring.
• Experience with machine learning platforms, real-time or streaming systems, large-scale experimentation, model governance, or AI and agentic systems.

Culture & Benefits

• Hybrid working model with day-to-day arrangements varying by organization and role.
• Inclusive, equitable, and inspiring workplace environment.
• Position eligible for equity.
• Base salary determined by location, travel, experience, skills, and expertise.

Hiring process

• Interviews assess foundational skills, collaboration, problem-solving approach, and how candidates work with AI.
• Candidates are expected to explain their reasoning and approach throughout the interview process.