Machine Learning Engineering Manager - Core Ads Ranking

The Team

The Core Ads Ranking team advances user representation and graph learning, improves sequence modeling across ads verticals, and builds robust pipelines and state‑of‑the‑art architectures for foundational models. The team also leads core initiatives in knowledge distillation, model calibration, and heuristic improvement.

This role offers a unique opportunity to shape and scale Reddit’s foundational modeling and deep user‑understanding roadmap, while multiplying impact through close collaboration with downstream teams including Retrieval, Shopping, Click Prediction, Video View‑Through Prediction, Conversion Prediction, and App Ads Modeling.

Responsibilities

• Set Technical Vision and Strategy: Define and execute a roadmap for foundational model and user understanding, balancing high-ambiguity long-term investments with measurable milestones.
• Collaborate Cross-Functionally: Partner with vertical customer teams, horizontal signal teams, and infrastructure/platform teams to align on direction, strategy, priorities, and constraints.
• Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance, reliability, and robustness.
• Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent while fostering a culture of growth, collaboration, and technical excellence.

Candidate Profile

• 1+ years of management experience leading ML-focused teams
• 6+ years of experience building and scaling machine learning models, and working with state-of-the-art machine learning models
• 4+ years of hands-on experience with TensorFlow or PyTorch
• End-to-End ML Lifecycle Experience: Proven ability in training, evaluating, and deploying large-scale models
• Experience working with foundational models, user or content understanding
• Experience with Ads is a plus

Interview & Application Notes

In select roles and locations, interviews will be recorded, transcribed, and summarized by artificial intelligence (AI). Candidates have the opportunity to opt out of recording, transcription, and summarization prior to any scheduled interviews.