Member of Technical Staff (Machine Learning Engineer, Ranking Quality - Search)

Perplexity
Belgrade, London, Berlin
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 5+ yearsSkills: ["Ownership","Cross-team collaboration","Problem-solving","Trade-off decision-making"]

Improve search quality across the middle and later stages of ranking by owning ranking-quality problems end to end—from evaluation and bottleneck analysis to building, shipping, and monitoring solutions. Train and evaluate retrieval, ranking, and classification models, including neural and LLM-based approaches. Build and operate ranking infrastructure for feature computation, low-latency inference, cascades, deployment, and trade-off decisions across quality, latency, reliability, and cost. Partner across Data, AI, Infrastructure, and Product.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Perplexity
Perplexity
7 hours ago

Member of Technical Staff (Machine Learning Engineer, Ranking Quality - Search)

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 7 hours agoStatus: Live

Job Summary

Improve search quality across the middle and later stages of ranking by owning ranking-quality problems end to end—from evaluation and bottleneck analysis to building, shipping, and monitoring solutions. Train and evaluate retrieval, ranking, and classification models, including neural and LLM-based approaches. Build and operate ranking infrastructure for feature computation, low-latency inference, cascades, deployment, and trade-off decisions across quality, latency, reliability, and cost. Partner across Data, AI, Infrastructure, and Product.
Location: Belgrade, London, Berlin
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Push search quality forward through models, data, evaluation, infrastructure, and other available levers.
  • •Own ranking-quality problems end to end: define evaluation, identify bottlenecks, build solutions, and ship safely.
  • •Train and evaluate retrieval, ranking, and classification models, including neural and LLM-based approaches where appropriate.
  • •Build and operate ranking infrastructure including feature computation, low-latency inference, cascades, deployment, and monitoring.
  • •Collaborate across Data, AI, Infrastructure, and Product while retaining ownership of the final quality outcome.

Key Requirements

  • •Deep understanding of search or recommender systems and their evaluation.
  • •Proven ownership of a large-scale production ranking system or a substantial class of quality problems.
  • •Strong machine-learning and software-engineering skills across data, models, serving, and monitoring.
  • •Drive ambiguous, cross-team problems without continuous task decomposition.
  • •Minimum 5 years of relevant industry experience.
Experience:5+ years
Skills:OwnershipCross-team collaborationProblem-solvingTrade-off decision-making
Tech Stack:Machine learningNeural rankingLLM-based approachesRetrieval modelsRanking modelsClassification modelsLow-latency inferenceDeploymentMonitoringFeature computationMulti-stage cascades

Company Brief

Perplexity
Perplexity AI provides an AI-powered answer engine that returns conversational, citation-backed answers to user queries and offers Pro/Enterprise products and APIs for research, knowledge work, and search augmentation.
Industry: AI & Machine Learning
Company Size: Medium (51 to 250 employees)
Revenue: USD 50M to 100M
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series D
Headquarters: San Francisco, United States
Founded: 2022
Glassdoor
Glassdoor: 4.6
WebsiteLinkedInGlassdoor