ML Engineering Manager, Core Ads Ranking

Reddit, Inc.; New York (NY); On-site; USD 230,000 - 322,000; Full time

Benefits offered by this job

Healthcare benefits

401k with employer match

Flexible vacation

Parental leave

Mental Health & Coaching Benefits

Job summary

Reddit, Inc. is seeking a proven ML leader to shape and scale its foundational modeling and user understanding roadmap. You will partner with cross-functional teams across Ads, Retrieval, Shopping, and Conversion Prediction to drive strategy, architecture, and robust ML systems.

You will mentor a high-performing team, oversee end-to-end model lifecycle from ideation to deployment, and balance long-term bets with tangible milestones, ensuring reliable, fair, and scalable AI for a global audience.

Qualifications

• Management experience leading ML teams.
• 6+ years of experience building and scaling ML models with state-of-the-art models.
• 4+ years hands-on experience with TensorFlow or PyTorch.
• End-to-End ML Lifecycle Experience: training, evaluating, and deploying large-scale models.
• Experience with foundational models, user or content understanding.
• Experience with Ads is a plus.

Responsibilities

• Set vision and roadmap for foundational models and user understanding with milestones.
• Partner with vertical customer teams, horizontal signal teams, and infra teams to align direction and priorities.
• Oversee the model development lifecycle from ideation to deployment with high ML performance and robustness.
• Recruit, mentor, and retain top ML talent while fostering growth and technical excellence.

Skills

Management experience

ML model scaling

Hands-on TF or PyTorch

Cross-functional collaboration

End-to-End ML lifecycle

Tools

TensorFlow

PyTorch

Job description

Reddit, Inc. is seeking a proven ML leader to shape and scale its foundational modeling and user understanding roadmap. You will partner with cross-functional teams across Ads, Retrieval, Shopping, and Conversion Prediction to drive strategy, architecture, and robust ML systems.

You will mentor a high-performing team, oversee end-to-end model lifecycle from ideation to deployment, and balance long-term bets with tangible milestones, ensuring reliable, fair, and scalable AI for a global audience.