Staff Machine Learning Engineer, Retrieval (Ads Retrieval)

Location: Remote - United States. A 100% remote opportunity is available; hybrid or onsite work is also supported from offices in New York, San Francisco, Los Angeles, and Chicago.

Base salary: $230,000–$322,000 USD per year, plus potential equity and, depending on the position, commission.

Company

Reddit operates a large-scale community platform with more than 100,000 active communities and approximately 130 million daily active unique visitors.

What you will do

• Set the technical direction and multi-year roadmap for ads retrieval modeling in partnership with engineering, product, data science, and advertising stakeholders.
• Design, develop, and launch candidate-generation and retrieval models for campaigns and ads across Reddit’s advertising surfaces.
• Apply two-tower architectures, representation learning, embeddings, sequence models, graph-based methods, and deep learning techniques.
• Improve objectives, labels, sampling, hard-negative mining, feature design, embedding generation, candidate filtering, and retrieval depth.
• Optimize approximate nearest-neighbor and vector retrieval systems across recall, relevance, freshness, diversity, coverage, latency, and cost.
• Lead offline analysis, online experiments, production launches, design reviews, code reviews, and mentoring for ML engineers.

Requirements

• 7+ years of industry experience, including substantial experience building and shipping applied machine learning products.
• Deep experience with information retrieval, candidate generation, recommender systems, ranking, or related relevance problems.
• Strong knowledge of DNNs, embeddings, two-tower or dual-encoder models, approximate nearest-neighbor search, and multi-stage retrieval.
• Experience training, evaluating, debugging, and deploying deep learning models with TensorFlow, PyTorch, or similar frameworks.
• Experience owning ML projects from problem framing and data preparation through offline evaluation, online experimentation, production launch, and iteration.
• Technical leadership, strong software engineering fundamentals, and excellent written and verbal communication.

Nice to have

• Experience with ads retrieval, ad serving, recommendation, search relevance, or marketplace optimization.
• Experience with sequential, graph, or multimodal modeling of users, content, campaigns, or ads.
• Experience connecting retrieval improvements to ranking, auctions, conversions, revenue, or user-experience outcomes.
• Publications, patents, or industry contributions in applied ML or ranking systems.

Culture & Benefits

• 100% remote work with hybrid and onsite options from four U.S. office locations.
• Comprehensive healthcare and income replacement programs.
• 401(k) with employer match and global benefit programs.
• Flexible vacation, paid volunteer time, and generous paid parental leave.
• Family planning, gender-affirming care, mental health, coaching, professional development, workspace, and caregiving support.

Hiring process

• Some interviews may be recorded, transcribed, and summarized by AI; candidates may opt out before scheduled interviews.