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

Perplexity

Belgrade, SerbiaJobNo compensation foundPosted 1w agoVerified open 4 days ago
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At a glance

Compensation
No compensation found
Location
Belgrade, Serbia
Work Authorization
Not specified

Job overview

Perplexity seeks an experienced Machine Learning Engineer to advance search quality in ranking stages. The role requires owning ambiguous problems end‑to‑end, with deep expertise in neural or low‑latency ranking systems, and the ability to design, build, and ship solutions across data, models, and infrastructure.

Skills & qualifications

RequiredNice to have

Skills

Machine LearningProduction SystemsSoftware EngineeringCollaborationProblem SolvingNeural RankingLLM Based ApproachesRanking InfrastructureFeature ComputationLow Latency InferenceMulti Stage CascadesData EngineeringModel DevelopmentModel ServingMonitoringEvaluation

Qualifications

Deep Understanding of Search or Recommender Systems and Their EvaluationProven Ownership of Large Scale Production Ranking System5+ Years Relevant Industry Experience

Full job description

Perplexity is seeking an experienced Machine Learning Engineer to improve search quality across the middle and later stages of ranking. We are looking for a strong ranking generalist who can own ambiguous problems end to end and brings exceptional depth in either neural ranking or production ranking systems.

Responsibilities

  • Relentlessly push search quality forward through models, data, evaluation, infrastructure, or any other leverage available.

  • Own ranking-quality problems end to end: define the evaluation, identify the bottleneck, build the solution, and ship it 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, multi-stage cascades, deployment, and monitoring.

  • Make sound trade-offs across quality, latency, reliability, cost, and engineering complexity.

  • Collaborate across Data, AI, Infrastructure, and Product while retaining ownership of the final quality outcome.

Qualifications

  • 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.

  • Ability to drive ambiguous, cross-team problems without continuous task decomposition.

  • Exceptional depth in either modern neural ranking methods or low-latency ranking systems and runtime.

  • Minimum 5 years of relevant industry experience.

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