Lead NLP Data Scientist - Search & Knowledge — Google

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Data Science · Verified Opening #3

Lead NLP Data Scientist - Search & Knowledge

business Google location_on Mountain View, CA (Hybrid) apartment Hybrid Full Time

Compensation

$195K – 275K/yr

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Published Date

2 weeks ago

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Work Arrangement

Hybrid • Mountain View, CA

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Open Positions

2 openings

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Experience Level

Lead

overview Role Overview

About the opportunity

Harness large-scale semantic parsing and text analytics to advance information retrieval quality for billions of users.

Google Search & Knowledge organization is seeking a Lead NLP Data Scientist. You will analyze complex semantic queries, evaluate semantic graph embeddings, and guide continuous ranking enhancements using transformer architectures and statistical quality signals. You will collaborate with research teams to translate NLP breakthroughs into production features.

task Core Responsibilities

What you will do

check_circle Develop statistical quality metrics and semantic evaluation benchmarks for multi-language search models.
check_circle Construct unsupervised clustering and entity extraction pipelines on billion-document corpora.
check_circle Lead cross-functional reviews evaluating model bias, factual accuracy, and latency trade-offs.
check_circle Guide engineering teams on training dataset curation and active learning loops.

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What we are looking for

arrow_circle_right MS or PhD in Computer Science, Computational Linguistics, or Statistics.
arrow_circle_right 6+ years experience focusing on Natural Language Processing and information retrieval systems.
arrow_circle_right Proficiency in PyTorch, TensorFlow, Python, and large distributed data processing tools.
arrow_circle_right Published research or demonstrable open-source contributions in NLP is highly valued.

code_blocks Technologies & Competencies

Skills & Tech Stack

NLP Transformers PyTorch Semantic Search Information Retrieval Python

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Why candidate applications stand out

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Verified Technical Credentials

Applications include direct proof-of-work repositories and instructor verification endorsements.

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Direct internal referral channels through enterprise partners bypass automated resume discard filters.

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Submit your résumé (PDF, DOC or DOCX up to 5 MB) for direct consideration by the Google hiring team.

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Cover Note

Google

Mountain View, CA (Hybrid)

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