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

Perplexity

Member of Technical Staff (Machine Learning Engineer, Ranking Quality - Search) is a still-open role at Perplexity on Jobrow. Location: On-site · Belgrade · Serbia. Sourced from the company's public Ashby board. First seen 2 months ago; last confirmed 9 days ago. Apply on the employer ATS — Jobrow is not the employer.

Pay
—
Workplace
On-site
Location
Belgrade · Serbia
First seen
2 months ago
Last seen
9 days ago
Board
Ashby
Apply

About this role

Perplexity is seeking an experienced Machine Learning Engineer to improve search quality across the middle and later stages of ranking.

  • Function: Machine learning
  • Seniority: staff

Location & pay

On-site · Belgrade · Serbia No pay range was listed on the public board feed.

Source

Jobrow reads the public Ashby board for Perplexity. First seen 2 months ago; last seen 9 days ago. We are not the employer — apply only on the company ATS.

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.

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