Staff Machine Learning Engineer (Shopping Ads)

Location: Remote within the United States

Salary: $230,000–$322,000 USD base salary, plus equity and potential commission depending on the position offered.

Company

Reddit operates a large community-driven social platform and develops commerce advertising products that connect advertisers with relevant audiences.

What you will do

• Lead the machine learning strategy and architecture for Shopping Ads across targeting, retrieval, ranking, engagement, conversion, and value optimization.
• Own the full model lifecycle, including opportunity sizing, data and label design, feature engineering, training, evaluation, experimentation, deployment, monitoring, and iteration.
• Build models that improve conversion, purchase value, revenue, return on ad spend, relevance, user experience, and marketplace health.
• Design shared features and representations using user intent, context, product catalog, advertiser, and historical interaction signals.
• Balance model quality with online latency, throughput, reliability, operational complexity, and serving cost.
• Coordinate complex initiatives across Ads, Catalog, ML Platform, Ads Serving, Auction, Bidding, Product, and Data Science teams while mentoring engineers and technical leads.

Requirements

• 7+ years of professional software or machine learning engineering experience, including substantial experience building applied ML systems in production.
• Experience delivering end-to-end models or model-driven products for advertising, recommendation, search, or marketplace optimization.
• Hands-on expertise in model development, complex feature engineering, training and evaluation pipelines, online inference, and experimentation.
• Experience with large-scale, high-throughput, low-latency ML systems and trade-offs among model quality, latency, reliability, and cost.
• Technical leadership experience setting direction, driving architecture and execution, mentoring engineers, and aligning cross-functional stakeholders.
• Must be based in the United States for this remote role.

Nice to have

• Experience with Shopping Ads, commerce advertising, Dynamic Product Ads, Product Listing Ads, product recommendation, or retail media.
• Experience with candidate retrieval, ranking, conversion modeling, value optimization, recommender systems, or representation learning.
• Experience with deep learning architectures such as multi-task models, sequence models, transformers, two-tower models, graph methods, or learned embeddings.
• Experience with catalog quality, product feeds, advertiser-side signals, delayed or sparse conversion labels, and online/offline distribution shift.
• Experience at a large-scale advertising, social, search, recommendation, e-commerce, or marketplace company.

Culture & Benefits

• Comprehensive healthcare benefits and income replacement programs.
• 401(k) with employer match.
• Flexible vacation, paid volunteer time off, and generous paid parental leave.
• Family planning support, gender-affirming care, and mental health and coaching benefits.
• Professional development, caregiving support, and other global benefit programs.
• Interviews may be recorded, transcribed, and summarized by AI, with the option to opt out before scheduled interviews.