Staff Machine Learning Engineer, Retrieval

Reddit
United States
Workplace: RemoteFull timeUSD 230,000 - 322,000 annuallyFunction: Data Science & Machine LearningSkills: ["Technical leadership","Experimental design","Model evaluation","Mentoring","Written and verbal communication"]

Lead technical direction for Reddit’s Ads Retrieval ML team, shaping a multi-year roadmap for retrieval modeling that improves relevance, advertiser outcomes, and user experience. Design, develop, and launch candidate-generation and retrieval models using modern deep learning approaches (e.g., two-tower architectures, embeddings, sequence/graph methods). Own evaluation practices and drive offline-to-online experimentation, partnering across ranking, ads platform, auction, and measurement teams to integrate effectively end-to-end.

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FursaFursa
Reddit
Reddit
14 hours ago

Staff Machine Learning Engineer, Retrieval

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Last checked: 3 hours agoStatus: Live

Job Summary

Lead technical direction for Reddit’s Ads Retrieval ML team, shaping a multi-year roadmap for retrieval modeling that improves relevance, advertiser outcomes, and user experience. Design, develop, and launch candidate-generation and retrieval models using modern deep learning approaches (e.g., two-tower architectures, embeddings, sequence/graph methods). Own evaluation practices and drive offline-to-online experimentation, partnering across ranking, ads platform, auction, and measurement teams to integrate effectively end-to-end.
Location: United States
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Define the technical direction and multi-year roadmap for ads retrieval modeling with engineering, product, data science, and ads stakeholders.
  • •Design, develop, and launch candidate-generation and retrieval models for campaigns and ads across Reddit advertising surfaces.
  • •Improve the retrieval stack across 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 to balance recall, relevance, freshness, diversity, coverage, latency, and cost trade-offs.
  • •Lead offline analysis and online experiments, translating results into the next modeling iteration and ensuring integration across the ads funnel.

Pay and Benefits

Salary: USD 230,000 - 322,000 annually
Equity and Bonus:Equity
Perks:Remote WorkHealth InsuranceDentalVision401kPaid ParentalLearning Budget

Key Requirements

  • •7+ years building and shipping applied ML products, with substantial applied ML experience.
  • •Deep expertise in information retrieval, candidate generation, recommender systems, ranking, and relevance problems.
  • •Strong retrieval modeling knowledge including DNNs, embeddings, two-tower/dual-encoder models, approximate nearest-neighbor search, and multi-stage retrieval.
  • •Experience training, evaluating, debugging, and deploying deep learning models using TensorFlow, PyTorch, or similar frameworks.
  • •Strong ownership from problem framing and data preparation through offline evaluation, online experimentation, production launch, and iteration.
Experience:Applied machine learningInformation retrievalRecommendationAdvertisingLarge-scale datasetsOffline and online experimentation
Skills:Technical leadershipExperimental designModel evaluationMentoringWritten and verbal communication
Languages:English
Tech Stack:TensorFlowPyTorchTwo-tower architecturesRepresentation learningEmbeddingsSequence modelsGraph-based methodsDeep learningApproximate nearest-neighborVector retrievalNearest-neighbor searchDNNDual-encoder modelsOffline and online experimentation

Company Brief

Reddit
Operates Reddit, a large online community and discussion platform where users submit content, comment, and vote across topic-based communities (subreddits); monetizes via advertising, premium subscriptions, and awards.
Industry: Digital Media
Company Size: Enterprise (1,001+ employees)
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: San Francisco, United States
Founded: 2005
WebsiteLinkedIn