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Chen Liang

@chenliang

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Senior machine learning engineer specializing in large-scale recommendation, NLP, and production ML systems.

United States

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What I'm looking for

I seek roles building and scaling production ML/NLP systems—recommendation, semantic search, or LLM workflows—with cross-functional collaboration, strong MLOps, and measurable user impact.

I am a senior machine learning engineer with deep experience building large-scale recommendation systems, transformer/NLP architectures, semantic search, and LLM-augmented workflows. I have led multi-model ranking pipelines and personalization systems that served over a billion users, drove statistically significant engagement gains via continuous A/B testing, and strengthened content integrity with transformer-based classifiers.

I collaborate closely with product, data, and engineering teams to deliver reliable MLOps infrastructure, monitoring, and rapid production troubleshooting. My background includes deploying semantic search prototypes, migrating search systems for large performance gains, implementing XGBoost and deep learning models, and automating end-to-end ML workflows to accelerate iteration and improve platform health.

Experience

Work history, roles, and key accomplishments

Current

Senior Machine Learning Engineer

Current

Instagram

Mar 2021 - Present (4 years 7 months)

Led development of a large-scale Home feed recommender for 1B+ users, built multi-model ranking pipelines and LLM-driven semantic search prototypes, and launched personalized ForYou feed rankings for Threads to improve engagement and retention through A/B testing.

Recommender Systems Semantic Search A B Testing MLOps Monitoring

Senior Data Scientist - Machine Learning

Coursera

Sep 2018 - Jan 2020 (1 year 4 months)

Built hybrid recommendation engines and XGBoost re-ranking models that increased engagement and enrollments, migrated email recommendation infrastructure to Python, and led A/B tests and discovery dashboards to optimize learner funnels.

Recommendation Systems XGBoost A B Testing Python Search Migration (Solr→Algolia)Dashboarding

Machine Learning Engineer

Oracle

Aug 2015 - Aug 2018 (3 years)

Developed k-NN prototypes and XGBoost models to prioritize QA bug triage, owned automated integration and statistical testing for enterprise analytics, and automated ML workflows to accelerate model iteration and deployment.

QA Automation XGBoost K NN CI CD Pyspark Monitoring Automated Testing

Data Scientist Intern

Shazam

Jun 2014 - Sep 2014 (3 months)

Analyzed 300M+ event records to model audio feature impacts on recognition by region, used geospatial clustering and dashboards to surface underperforming markets and guide algorithm improvements.

Clustering Dashboarding Data Pipelines Performance Monitoring