Staff Machine Learning Engineer, Retrieval

atReddit, Inc.Remote

United States Full-time Machine Learning EngineerLead$230k – $322k/year

Posted 9 hours ago

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

📋 Description

• Establish the technical strategy and multi-year roadmap for advertising retrieval modeling.

• 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 deep learning approaches.

• Enhance objectives, labels, sampling techniques, hard-negative mining, feature design, embedding generation, candidate filtering, and retrieval depth.

• Collaborate with approximate nearest-neighbor and vector retrieval systems.

• Assess recall, relevance, freshness, diversity, coverage, latency, and cost trade-offs.

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

• Lead offline analyses and online experiments, translating results into modeling revisions.

• Collaborate with ranking, ads platform, auction, measurement, and product teams.

• Compose design documents, review code and model modifications, and enhance modeling, testing, observability, and production ownership.

• Guide ML engineers and cultivate expertise in retrieval, recommendation, and representation learning.

⛳️ Requirements

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

• Extensive background in information retrieval, candidate generation, recommender systems, ranking, or related relevance challenges.

• Strong knowledge of DNN, embeddings, two-tower or dual-encoder models, approximate nearest-neighbor search, and multi-stage retrieval.

• Profound experience in training, evaluating, debugging, and deploying deep learning models using frameworks like TensorFlow, PyTorch, or similar.

• Proven ownership of ML projects from problem definition and data preparation to offline evaluation, online experimentation, production launch, and iteration.

• Excellent understanding of experimental design and model evaluation.

• Experience working with large-scale behavioral, contextual, or content datasets and intricate feature pipelines.

• Solid software engineering principles and the capability to write clear, reliable, and maintainable production code.

• Demonstrated technical leadership, including setting direction, managing complex projects, influencing partner teams, and mentoring engineers.

• Exceptional written and verbal communication skills.

• Preferred: experience in ads retrieval, ad serving, recommendation, search relevance, marketplace optimization, sequential/graph/multimodal signals, ads marketplaces, publications/patents/industry contributions, and sequential modeling.