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

Belgrade, Serbia

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Work setup
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Employment
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Apply at Perplexity

What you’ll work on

Full posting
  • Own ranking-quality problems end to end: define the evaluation, identify the bottleneck, build the solution, and ship it safely.

  • Build and operate ranking infrastructure, including feature computation, low-latency inference, multi-stage cascades, deployment, and monitoring.

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

From the employer’s posting
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.
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.
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

What you’ll bring

All qualifications

Core experience

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

Job description

View original posting ↗

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

  • 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.

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

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Location & working pattern

Belgrade, Serbia

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Status in our records
Active
First seen by us
Aug 13, 2026
Recorded sightings
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Last seen by us
Oct 9, 2026

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