Congmin Min

ML Engineer

https://www.opentalent.in/congmin-min

Principle NLP Engineer at Weibo R&D Limited

Key Strengths

Extensive experience (20+ years) in Natural Language Processing (NLP) and Machine Learning (ML).
Deep expertise in building knowledge graphs, document tagging, recommendation systems, and intelligent assistants.
Proficiency in deep learning, deep language parsing, and statistical language models.
Strong background in Named Entity Recognition (NER), Relation Extraction, and sentiment analysis.
Direct experience with Graph Neural Networks (GNN) for graph embedding and recommendation.
Significant experience in multi-lingual NLU and e-commerce dialog assistants.
Academic background in Information Science and Computational Linguistics directly aligns with ML Engineer role.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate has a long and varied career path, working in both established companies (Weibo, Midea) and AI-focused startups (Beyond AI, JD American Technologies). This diversity suggests an ability to adapt to different organizational cultures and project scopes. The consistent focus on NLP and ML across roles indicates a strong passion and dedication to the field, which aligns well with a specialized ML Engineer role. However, the lack of explicit project details makes it hard to assess specific contributions to team environments or broader cultural alignment.

Soft Skills & Operational Fit

The candidate's extensive experience across various companies and roles suggests adaptability and a strong problem-solving orientation. The descriptions imply a focus on research and development, indicating an ability to work on complex, innovative projects. However, without specific project details or team collaboration examples, it's difficult to assess soft skills like leadership, teamwork, or communication beyond what's inferred from role descriptions.

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About

Research and hands-on experiences in a wide range of NLP problems in multiple domains. Experienced in applying modern deep learning and machine learning algorithms and libraries to build models for multilingual text analysis. The application areas I have worked on include chatbot, intelligent assistant, social media analytics, sentiment analysis, demographic classification, scientific and research literature analysis, news domain.

Top Skills

Data AnnotationLinguisticsE-commercePyTorchTensorFlowArtificial Intelligence (AI)Deep LearningMachine LearningNatural Language ProcessingText MiningInformation RetrievalLuceneLinuxInformation ExtractionSentiment AnalysisComputational linguisticsmachine translationSemantic SearchJavaWeb MiningBig DataAlgorithmsData sciencetext-classificationNlpHuman-Computer InteractionSpeech RecognitionrdfPattern RecognitionScalabilityKnowledge Representationparsing

Education

Georgetown University

M.S., Computational Linguistics

January 1, 2003 – January 1, 2005

Peking University

M.S., Information Science

January 1, 1999 – January 1, 2002

Civil Aviation University of China

B. A., Linguistics

January 1, 1995 – January 1, 1999

Experience

Weibo R&D Limited

Principle NLP Engineer

December 1, 2019 – Present

Hybrid

Beyond AI

Senior Scientist

March 1, 2019 – November 1, 2019

United States

JD American Technologies

Senior NLP Scientist

April 1, 2017 – March 1, 2019

Mountain View, CA

Midea Group (Fortune Global 500 Company)

Staff Artificial Intelligence Engineer

December 1, 2016 – April 1, 2017

Santa Clara, CA

NetBase Solutions, Inc.

Senior Computational Linguist

February 1, 2008 – November 1, 2016

Mountain View, CA

Language Computer Corporation

NLP Software Engineer

March 1, 2006 – February 1, 2008

Key Strengths

Extensive experience (20+ years) in Natural Language Processing (NLP) and Machine Learning (ML).
Deep expertise in building knowledge graphs, document tagging, recommendation systems, and intelligent assistants.
Proficiency in deep learning, deep language parsing, and statistical language models.
Strong background in Named Entity Recognition (NER), Relation Extraction, and sentiment analysis.
Direct experience with Graph Neural Networks (GNN) for graph embedding and recommendation.
Significant experience in multi-lingual NLU and e-commerce dialog assistants.
Academic background in Information Science and Computational Linguistics directly aligns with ML Engineer role.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit