Staff Machine Learning Engineer, Retrieval & Targeting

This is a fully remote position, open to applicants in United States.

📋 Description

• Establish the technical direction and long-term roadmap for ads retrieval modeling in collaboration with engineering, product, data science, and advertising stakeholders.

• Create, develop, and implement candidate-generation and retrieval models for campaigns and advertisements across Reddit’s advertising platforms.

• Utilize two-tower architectures, representation learning, embeddings, sequence models, graph-based techniques, and various deep learning methodologies.

• Enhance objectives, labeling, sampling techniques, hard-negative mining, feature engineering, embedding creation, candidate filtering, and retrieval depth.

• Collaborate with approximate nearest-neighbor and vector retrieval systems, optimizing recall, relevance, freshness, diversity, coverage, latency, and cost.

• Develop evaluation practices that link retrieval metrics to advertising performance and user outcomes.

• Conduct offline analyses and online experiments, translating results into modeling improvements.

• Partner with teams focused on downstream ranking, advertising platforms, auctions, measurement, and product development.

• Compose design documentation, review code and model modifications, and enhance modeling, testing, observability, and production management.

• Mentor machine learning engineers and expand the team’s expertise in retrieval, recommendation, and representation learning.

⛳️ Requirements

• Over 7 years of industry experience, including significant expertise in building and deploying applied machine learning products.

• Extensive experience with information retrieval, candidate generation, recommender systems, ranking, or related relevance challenges.

• Profound understanding of deep neural networks, embeddings, two-tower or dual-encoder models, approximate nearest-neighbor searches, and multi-stage retrieval processes.

• Comprehensive experience in training, assessing, debugging, and deploying deep learning models using TensorFlow, PyTorch, or comparable frameworks.

• Proven ownership of machine learning projects from problem identification and data preparation to offline evaluation, online experimentation, production implementation, and iterative improvements.

• Strong grasp of experimental design and model evaluation methodologies.

• Experience handling large-scale behavioral, contextual, or content datasets alongside complex feature pipelines.

• Solid software engineering fundamentals with the ability to produce clear, reliable, and maintainable production code.

• Technical leadership experience, including defining direction, managing complex projects, influencing partner teams, and mentoring engineers.

• Exceptional written and verbal communication skills.

• Preferred: background in ads retrieval, ads ranking, ad targeting, ad serving, recommendation systems, search relevance, or marketplace optimization.

• Preferred: experience in modeling interactions using sequential, graph, or multimodal signals.

• Preferred: ability to connect retrieval enhancements to ranking, auction, conversion, revenue, or user experience outcomes.

• Preferred: familiarity with ads marketplaces at peer organizations.

• Preferred: publications, patents, or contributions to the field of applied machine learning or ranking systems.

• Preferred: experience with sequential modeling techniques such as RNNs or Transformers.

🏝️ Benefits

• 100% remote work opportunity.

• Comprehensive healthcare benefits and income replacement programs.

• 401k plan with employer matching.

• Global benefits programs tailored to fit your lifestyle, including workspace options, professional development, and caregiving support.

• Family planning assistance.

• Gender-affirming healthcare options.

• Mental health and coaching benefits.

• Flexible vacation policy and paid volunteer time off.

• Generous paid parental leave.

• Equity in the form of restricted stock units.

• Potential eligibility for commission based on the position offered.

• Medical, dental, and vision insurance coverage.

• Interview recording opt-out option available.

• Reasonable accommodations for qualified individuals with disabilities and disabled veterans.