Staff Machine Learning Engineer, Shopping Ads

Reddit
United States
Workplace: RemoteFull timeUSD 230,000 - 322,000 annuallyFunction: Data Science & Machine LearningExperience: 7+ yearsSkills: ["Communication","Mentoring","Collaboration"]

Lead end-to-end machine learning strategy and execution for Shopping Ads, driving model quality and impact across targeting, retrieval, ranking, engagement, and conversion/value optimization. Own the full lifecycle from data/label design and feature engineering to offline evaluation, online experimentation, deployment, monitoring, and iteration. Balance relevance and measurable advertiser outcomes while improving latency, reliability, and serving cost across multiple ads and data systems.

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FursaFursa
Reddit
Reddit
4 days ago

Staff Machine Learning Engineer, Shopping Ads

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 5 hours agoStatus: Live

Job Summary

Lead end-to-end machine learning strategy and execution for Shopping Ads, driving model quality and impact across targeting, retrieval, ranking, engagement, and conversion/value optimization. Own the full lifecycle from data/label design and feature engineering to offline evaluation, online experimentation, deployment, monitoring, and iteration. Balance relevance and measurable advertiser outcomes while improving latency, reliability, and serving cost across multiple ads and data systems.
Location: United States
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Sr. Manager level

Key Responsibilities

  • •Lead ML strategy and architecture for Shopping Ads delivery across targeting, retrieval, ranking, engagement, conversion, and value optimization.
  • •Own end-to-end model development from opportunity sizing and data/label design through feature engineering, offline evaluation, online experimentation, deployment, monitoring, and iteration.
  • •Build and optimize models for low-funnel advertiser objectives while maintaining relevance, user experience, marketplace health, and measurement quality.
  • •Develop feature and representation strategies connecting user intent/context, product catalog signals, advertiser signals, and historical interactions across multiple delivery models.
  • •Drive cross-team initiatives across Shopping Ads systems, setting a high technical bar through architecture reviews, experimentation standards, production ownership, observability, and model-quality practices.

Pay and Benefits

Salary: USD 230,000 - 322,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceIncome Replacement401kEmployer MatchDentalVisionFamily PlanningPaid LeaveParental LeavePaid VolunteerCaregiving Support

Key Requirements

  • •7+ years of professional software or machine learning engineering experience, including building applied ML systems in production.
  • •Proven ability to build end-to-end models or model-driven products that improve advertising, recommendation, search, or marketplace performance.
  • •Experience optimizing low-funnel objectives (e.g., conversion, purchase value, revenue, ROAS) using outcome-based metrics.
  • •Strong hands-on experience with model development, complex feature engineering, training/evaluation pipelines, online inference, and experimentation.
  • •Proven technical-lead experience setting direction, driving architecture and execution, mentoring engineers, and influencing cross-functional stakeholders.
Experience:7+ years
Skills:CommunicationMentoringCollaboration
Tech Stack:TransformersTwo-tower modelsGraph methodsLearned embeddingsMulti-task modelsSequence models

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