Matthew Wang
@matthewwang
Senior Machine Learning Engineer building large-scale recommendation and personalization systems with deep learning and MLOps excellence.
United StatesWhat I'm looking for
I’m a Senior Machine Learning Engineer with experience building large-scale recommendation, ranking, and personalization systems at Pinterest and Meta. I combine user behavior signals, catalog metadata, and embeddings to improve relevance and conversion in production environments.
Across my roles, I’ve developed multi-stage retrieval and ranking pipelines and multimodal ML models using computer vision and transformer-based architectures, including LLM-assisted retrieval. I design real-time and batch feature engineering workflows using distributed data platforms to process high-volume behavioral and catalog data reliably.
I productionize low-latency ML services and drive dependable MLOps practices—MLflow, CI/CD, experiment tracking, monitoring, drift detection, automated retraining, and observability. I also lead A/B testing and ranking evaluation using statistical and causal analysis, partnering cross-functionally to deliver safe, scalable AI-driven product impact.
Experience
Work history, roles, and key accomplishments
Architected large-scale Shopping Ads and Visual Discovery ranking systems by combining user behavior signals, catalog metadata, and image embeddings. Built multi-stage retrieval/ranking pipelines and multimodal models in PyTorch/TensorFlow, and productionized low-latency ML services with Kubernetes and gRPC while improving reliability through MLOps and A/B testing.
Contributed to large-scale Feed and recommendation ranking systems by improving model features, ranking logic, and personalization workflows. Built scalable ML pipelines and NLP/embedding-based content understanding models, supported production deployment with monitoring/optimization, and evaluated ranking changes using A/B testing.
Developed predictive ML solutions for enterprise AI products, including forecasting and anomaly detection, and enabled operational decision-making across client datasets. Built end-to-end ML pipelines using Python, Spark, SQL, XGBoost, and scikit-learn, supported AWS deployment, and improved model quality and delivery efficiency through experimentation and production-focused engineering.
Developed data science and machine learning solutions for enterprise clients using statistical modeling and predictive analytics to improve decision-making. Built analytical workflows in Python/SQL/Pandas/scikit-learn/Spark, automated reporting and data cleaning, and presented insights to technical and non-technical stakeholders.
Education
Degrees, certifications, and relevant coursework
San Diego State University
Master's Degree in Computer Science, Computer Science
2014 - 2016
Earned a master's degree in computer science at San Diego State University from 2014 to 2016.
Availability
Location
United StatesAuthorized to work in
Job categories
Skills
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