Staff Machine Learning Engineer, Retrieval

Reddit, Inc.

. Define the technical direction and multi-year roadmap for ads retrieval modeling .

Posted 9/16/2026full-timeRemote • United StatesLead💰 $230,000 - $322,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in defining technical direction and developing advanced ads retrieval models, leveraging deep learning techniques and information retrieval methodologies. Proven ability to lead projects from conception through deployment while mentoring teams and ensuring high-quality production standards.

Highest-signal resume keywords

Deep Learning Model DevelopmentInformation Retrieval ExpertiseTensorFlow or PyTorch ProficiencyTechnical Leadership ExperienceExperimental Design and Model Evaluation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Ads Retrieval ModelingCandidate GenerationRecommender SystemsDNN and EmbeddingsTwo-Tower ArchitecturesApproximate Nearest-Neighbor SearchModel EvaluationFeature DesignProduction Code DevelopmentData Preparation

Soft Skills

Excellent Written CommunicationExcellent Verbal CommunicationMentoring

Tools & Technologies

TensorFlowPyTorchVector Retrieval SystemsBehavioral DatasetsContextual DatasetsContent Datasets

Industry Keywords

Ads MarketplacesSearch RelevanceMarketplace OptimizationSequential ModelingGraph-Based Methods

Tech Stack

Tools & technologies

PyTorchTensorflow

About the role

Key responsibilities & impact

Define the technical direction and multi-year roadmap for ads retrieval modeling
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 strategies, hard-negative mining, feature design, embedding generation, candidate filtering, and retrieval depth
Work with approximate nearest-neighbor and vector retrieval systems
Evaluate recall, relevance, freshness, diversity, coverage, latency, and cost trade-offs
Establish evaluation practices connecting retrieval metrics to ads and user outcomes
Lead offline analysis and online experiments and translate findings into modeling iterations
Partner with ranking, ads platform, auction, measurement, and product teams
Write design documents, review code and model changes, and improve modeling, testing, observability, and production ownership
Mentor ML engineers and grow expertise in retrieval, recommendation, and representation learning

Requirements

What you’ll need

7+ years of industry experience, including substantial experience building and shipping applied ML products
Deep experience with information retrieval, candidate generation, recommender systems, ranking, or related relevance problems
Strong understanding of DNN, embeddings, two-tower or dual-encoder models, approximate nearest-neighbor search, and multi-stage retrieval
Deep experience training, evaluating, debugging, and deploying deep learning models using TensorFlow, PyTorch, or similar frameworks
Demonstrated ownership of ML projects from problem framing and data preparation through offline evaluation, online experimentation, production launch, and iteration
Strong command of experimental design and model evaluation
Experience with large-scale behavioral, contextual, or content datasets and complex feature pipelines
Strong software engineering fundamentals and ability to write clear, reliable, maintainable production code
Technical leadership experience, including setting direction, leading complex projects, influencing partner teams, and mentoring engineers
Excellent written and verbal communication
Preferred: experience with ads retrieval, ad serving, recommendation, search relevance, marketplace optimization, sequential/graph/multimodal signals, ads marketplaces, publications/patents/industry contributions, and sequential modeling

Benefits

Comp & perks

100% remote opportunity
Comprehensive Healthcare Benefits and Income Replacement Programs
401k with Employer Match
Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Paid Volunteer Time Off
Generous Paid Parental Leave
Equity in the form of restricted stock units
Medical, dental, and vision insurance
AI interview recording opt-out option
Reasonable accommodations for qualified individuals with disabilities and disabled veterans