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Quora

Staff Machine Learning Engineer, Recommendation Systems

Quora

. Define the technical direction for Quora’s home feed recommendation systems .

Posted 10/23/2026full-timeRemote • United StatesLead💰 $219,989 - $320,613 per yearWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in machine learning systems, particularly in building and optimizing recommendation systems for social media platforms. Proficient in leading large-scale ML projects, mentoring teams, and driving measurable improvements in user engagement through innovative AI-assisted development.

Highest-signal resume keywords
Machine Learning SystemsRecommendation Systems OptimizationPython or C++ ProgrammingEnd-to-End Project LeadershipData Pipeline Management

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
Machine LearningCandidate GenerationRankingRe-RankingMulti-Objective OptimizationFeature EngineeringModel TrainingProduction IntegrationData PipelinesMathematical Foundations of Algorithms
Soft Skills
Strong CommunicationInterpersonal SkillsMentoringTeam CollaborationPositive Attitude
Tools & Technologies
AI-Assisted DevelopmentGenerative ModelsOnline ExperimentationUser Engagement MetricsContent Quality Improvement
Certifications & Qualifications
BS in Computer ScienceMS in Computer SciencePhD in Computer Science
Industry Keywords
Social MediaUser-Generated ContentGrowth ModelingLifecycle ModelingNotificationsEmail Recommendations

Tech Stack

Tools & technologies
PythonC++

About the role

Key responsibilities & impact
  • Define the technical direction for Quora’s home feed recommendation systems
  • Lead high-impact projects across the recommender stack, from candidate generation and retrieval through ranking, re-ranking, and multi-objective optimization
  • Drive measurable improvements in user engagement and content quality through online experiments
  • Own ML systems end-to-end, including data pipelines, candidate extraction, feature engineering, model training, and production integration
  • Identify opportunities to apply machine learning across the Quora product
  • Partner with product, data science, and infrastructure teams on priorities and tradeoffs
  • Mentor engineers and raise standards for code quality, modeling rigor, and AI-assisted development velocity
  • Write production code as a high-leverage individual contributor
  • Shape how the team uses AI-assisted development to accelerate shipping velocity
  • Work on the Quora product, including recommendation surfaces such as notifications and digest emails

Requirements

What you’ll need
  • Availability for meetings and impromptu communication during Quora’s coordination hours, Monday–Friday, 9am–3pm Pacific Time
  • 6+ years of professional software development experience in machine learning
  • 4+ years of professional experience building and optimizing Home Feed recommendation systems for social media and user-generated content platforms
  • Deep knowledge of candidate generation, retrieval, ranking, re-ranking, embeddings, and multi-objective optimization
  • Deep understanding of the mathematical foundations of machine learning algorithms
  • Experience leading large-scale ML projects end-to-end with measurable outcomes
  • Strong communication and interpersonal skills
  • BS, MS, or PhD in Computer Science
  • Preferred: 6+ years of experience writing Python or C++ code
  • Preferred: Hands-on experience deploying and running generative models at scale
  • Preferred: Background in notifications, email/digest recommendations, or growth and lifecycle modeling
  • Preferred: Flexible and positive team player
  • Preferred: Publications at venues such as RecSys, KDD, NeurIPS, or ICML
  • Preferred: Passion for Quora’s mission and goals
  • Must complete identity verification and a comprehensive background check prior to onboarding

Benefits

Comp & perks
  • Medical, dental, and vision coverage
  • Equity refreshers
  • Remote work reimbursement
  • Paid time off
  • Employee assistance programs
  • Flexible equity program in equity-eligible countries, allowing a portion of equity compensation to be taken as cash
  • Benefits vary by country
  • Identity verification and comprehensive background check prior to onboarding