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

The role

This person will improve search quality across the middle and later stages of ranking. They will own ranking-quality problems end to end by defining evaluation, identifying bottlenecks, building solutions, and shipping them.

What you will do

• Push search quality forward through models, data, evaluation, infrastructure, or other leverage.
• Own ranking-quality problems end to end.
• Train and evaluate retrieval, ranking, and classification models.
• Build and operate ranking infrastructure including feature computation, low-latency inference, multi-stage cascades, deployment, and monitoring.
• Make trade-offs across quality, latency, reliability, cost, and engineering complexity.
• Collaborate across Data, AI, Infrastructure, and Product.

Required 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.

About the company

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