Member of Technical Staff (Machine Learning Engineer, Ranking Quality - Search)
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At a glance
Job overview
Perplexity is hiring a Member of Technical Staff (Machine Learning Engineer, Ranking Quality - Search). Perplexity is seeking an experienced Machine Learning Engineer to improve search quality across the middle and later stages of ranking, looking for a strong ranking generalist who can own ambiguous problems end‑to‑end and bring exceptional depth in neural or production ranking systems.
Key focus areas include 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, and Train and evaluate retrieval, ranking, and classification models, including neural and LLM‑based approaches where appropriate.
Important skills include Machine Learning, Neural Ranking, LLM-Based Approaches, Retrieval Models, Ranking Models, and Classification Models.
Skills & qualifications
Skills
Qualifications
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
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Relentlessly push search quality forward through models, data, evaluation, infrastructure, or any other leverage available.
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Own ranking-quality problems end to end: define the evaluation, identify the bottleneck, build the solution, and ship it safely.
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Train and evaluate retrieval, ranking, and classification models, including neural and LLM-based approaches where appropriate.
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Build and operate ranking infrastructure, including feature computation, low-latency inference, multi-stage cascades, deployment, and monitoring.
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Make sound trade-offs across quality, latency, reliability, cost, and engineering complexity.
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Collaborate across Data, AI, Infrastructure, and Product while retaining ownership of the final quality outcome.
Qualifications
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Deep understanding of search or recommender systems and their evaluation.
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Proven ownership of a large-scale production ranking system or a substantial class of quality problems.
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Strong machine-learning and software-engineering skills across data, models, serving, and monitoring.
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Ability to drive ambiguous, cross-team problems without continuous task decomposition.
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Exceptional depth in either modern neural ranking methods or low-latency ranking systems and runtime.
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Minimum 5 years of relevant industry experience.
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