Remote Staff ML Engineer - Ads Delivery & Optimization

Reddit, Inc.; United States; Remote; USD 150,000 - 230,000; Full time

Job summary

Reddit, Inc. is seeking a Staff Machine Learning Engineer to lead the technical strategy for Shopping Ads delivery. You will oversee end-to-end model development, targeting, retrieval, ranking and conversion prediction to improve advertiser outcomes.

This remote role demands strong leadership, data design, feature engineering, deployment, and management of large-scale ML systems, balancing quality with operational efficiency across cross-functional teams.

Qualifications

• 7+ years of professional experience in software or machine learning engineering with a focus on applied ML systems.
• Demonstrated experience in building end-to-end models that improve advertising or marketplace performance.
• Strong hands‑on experience with model development, feature engineering, and online inference.
• Proven technical leadership experience, including mentoring and influencing cross-functional teams.
• Deep understanding of large-scale ML systems and the trade‑offs between model quality and operational efficiency.

Responsibilities

• Lead the ML strategy and architecture for Shopping Ads delivery across various components.
• Own the complete model development process, including data design, feature engineering, and deployment.
• Drive complex initiatives requiring coordination across multiple teams and systems.

Skills

7+ years experience

End-to-end model development

Online inference

Technical leadership

Large-scale ML systems

Job description

Reddit, Inc. is seeking a Staff Machine Learning Engineer to lead the technical strategy for Shopping Ads delivery. You will oversee end-to-end model development, targeting, retrieval, ranking and conversion prediction to improve advertiser outcomes.

This remote role demands strong leadership, data design, feature engineering, deployment, and management of large-scale ML systems, balancing quality with operational efficiency across cross-functional teams.