Senior Machine Learning Engineer

Reddit, Inc.

full-time

Posted on: 8/14/2025

Location: 🇺🇸 United States

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💰 $216,700 - $303,400 per year

Senior

AndroidDistributed SystemsiOSKafkaPythonPyTorchScalaSparkTensorflow

About the role

Reddit is a community of communities; it’s built on shared interests, passion, and trust and is home to the most open and authentic conversations on the internet. Reddit has a flexible workforce and remote work options; you can apply to work remotely in any country in which Reddit has a physical presence.\n
Reddit Ads encompasses teams like Ads ML Serving, Attribution & Identity, Ads Measurement Modeling, Ads Targeting & Retrieval, Advertiser Optimization, Ads Marketplace Quality, App Ads and Conversion Modeling, Ads Prediction.\n
Role: Machine Learning Engineer on the Ads team, responsible for the full lifecycle of ML systems from research to production.\n
Responsibilities: design, build, deploy ML models for ad ranking, bidding, and optimization; own ML lifecycle; feature engineering; cross-functional collaboration; monitoring and retraining pipelines; research new algorithms.\n
Required Qualifications: 3+ years of experience; programming in Python/Scala; TensorFlow or PyTorch; cross-functional collaboration; KPI-driven ML impact.\n
Pay Transparency: base pay range $216,700–$303,400 USD; comprehensive benefits.\n
Reddit’s mission: empower communities and deliver relevant ads while respecting privacy and compliance.

At least 3+ years of end-to-end experience in training, evaluating, and deploying machine learning models in a production environment.\n
Proficient in one or more general-purpose programming languages (e.g., Python, Scala) and have a solid understanding of software development best practices.\n
Hands-on experience with a major machine learning framework (e.g., TensorFlow, PyTorch) and a deep understanding of core ML concepts and algorithms.\n
Proven ability to work effectively with cross-functional teams, including product managers and data scientists, to translate business needs into technical solutions.\n
Track record of using machine learning to drive key performance indicator (KPI) wins and solve complex, real-world problems.