Bupt A.

Key Skills

Software

No software listed

Top Subject Matter

Map-domain NLP (entity extraction, search/query understanding, content understanding)

Top Data Types

Text

Top Task Types

Entity (NER) Classification

Freelancer Overview

NLP Algorithm Engineer / NLP Algorithm Lead (Tencent Technology) — annotation schema & labeling QA for NER/sequence labe. Brings 7+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Engineering, Beijing University of Posts and Telecommunications (2008). AI-training focus includes data types such as Text and labeling workflows including Entity (NER) Classification and Named Entity Recognition.

Labeling Experience

NLP Algorithm Engineer / NLP Algorithm Lead - Tencent Technology (Beijing) Co., Ltd.

TextEntity (NER) Classification

Led and participated in the deployment of NLP technologies for map-domain scenarios, covering entity understanding, place-related information extraction, and content/query processing. Built and optimized named entity recognition and sequence labeling models using deep learning and TensorFlow training workflows, with iteration driven by error analysis and production feedback. Developed scalable Spark-based data pipelines for text processing, sample mining, feature preparation, and offline evaluation to support continuous model improvement. • Led map-domain NLP capability landing, coordinating across stakeholders to improve search and content understanding. • Designed and trained NER/sequence-labeling models with TensorFlow, focusing on precision/recall and label refinement. • Implemented large-scale Spark pipelines for dataset generation, sample mining, and offline benchmarking. • Managed NLP technical delivery including roadmap planning, task breakdown, mentoring, and technical reviews.

2017 - 2023

NLP Algorithm Engineer / NLP Algorithm Lead (Tencent Technology) — annotation schema & labeling QA for NER/sequence labeling

TextEntity (NER) Classification

Led annotation schema design and guideline calibration for map-domain NLP tasks, supporting entity understanding and sequence labeling. Built labeling workflows covering trial annotation, batch labeling, quality inspection, and rework management to improve dataset reliability. Implemented acceptance criteria based on inter-annotator consistency, entity boundary accuracy, and category correctness, including coverage for long-tail edge cases. • Designed label taxonomy, boundary rules, ambiguity handling, negative samples, and edge-case definitions • Trained and guided annotators on task objectives, labeling criteria, difficult cases, and quality expectations • Performed sampling inspection, consistency checks, dispute review, and gold-standard dataset creation with feedback loops • Coordinated guideline and evaluation set updates driven by model error analysis (false positives/false negatives)

2017 - 2023

Education

Work History