Machine Learning Manager - Ads Retrieval

The Ads Retrieval team is dedicated to identifying and sourcing the most relevant, engaging, and high-quality ad candidates from a vast pool of possibilities. By building and refining large-scale indexing and retrieval systems capable of handling millions to billions of candidates—and leveraging advanced machine learning models and infrastructure—we enable optimal downstream ranking and delivery. As we evolve Reddit’s advertising business, the Ads Retrieval team plays a critical role in ensuring a strong supply of relevant ads that meet both user engagement goals and advertiser performance targets. We are seeking a Manager with deep ML expertise, strategic vision, and strong leadership to define and execute the team’s roadmap.

Responsibilities:

• Set Technical Vision & Strategy: Define and execute a comprehensive roadmap for ads retrieval that balances innovation, efficiency, and business impact.
• Oversee Model & System Development: Guide the end-to-end ML model development process—from data processing and training to deployment—and ensure the retrieval systems are robust and scalable.
• Mentor & Grow Your Team: Recruit, mentor, and retain top ML talent while fostering a collaborative, inclusive, and high-performing culture.
• Cross-Functional Collaboration: Partner with Product Managers, Data Scientists, and other engineering teams to align retrieval strategies with product requirements and key performance indicators (KPIs).
• Continuous Improvement: Advocate for model quality, system reliability, and operational excellence. Identify and implement opportunities to enhance ML engineer productivity and overall team performance.

Requirements:

• At least 2 years of engineering management experience, leading ML or related technical teams.
• A minimum of 6 years of experience with large-scale ML, ideally in information retrieval, recommendation systems, or advertising.
• At least 4 years of hands-on experience with ML frameworks such as TensorFlow or PyTorch.
• Proven experience deploying ML models to production and measuring their performance using both technical and business metrics.
• Familiarity with advertising ecosystems, marketplace dynamics, and candidate retrieval processes is a significant plus.

Benefits:

• Comprehensive Health benefits
• Retirement Savings plan with matching contributions
• Workspace benefits for your home office
• Personal & Professional development funds
• Family Planning Support
• Flexible Vacation & Reddit Global Days Off

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