Xingtai Li
@xingtaili1
Senior Machine Learning Engineer specializing in GenAI, LLMs, and production MLOps.
What I'm looking for
I am a Senior Machine Learning Engineer with 8+ years building and deploying large-scale AI systems across generative, predictive, and real-time domains, combining research innovation with production-grade engineering to deliver measurable impact.
I have led development of generative models, LLM orchestration, and cloud-native MLOps—optimizing diffusion training, implementing RAG and multi-agent systems, and building end-to-end ML platforms that power millions of users while improving deployment speed, reliability, and personalization.
Experience
Work history, roles, and key accomplishments
Built generative AI models (Firefly) and LLM-based assistants, optimizing diffusion training/inference to scale to 7B+ creations and delivering secure, production-ready generative workflows used by millions.
Built Nordstrom's core ML platform to automate training, deployment, and monitoring, reduced deployment time from weeks to minutes, and delivered real-time pipelines powering recommendations and fraud detection for millions of users.
Machine Learning Engineer
Confidential
Jul 2017 - Sep 2019 (2 years 2 months)
Built large-scale Spark/Kafka ML pipelines for insurance pricing, fraud, and claims prediction, implemented real-time risk scoring and CV models that reduced claim cycle time by 40% and automated inspections.
Education
Degrees, certifications, and relevant coursework
University of California, Davis
Master of Science, Computer Science and Statistics
2015 - 2017
Completed a master's program combining computer science and statistics with coursework and projects focused on machine learning and data analysis.
University of Wisconsin-Madison
Bachelor of Science, Biological System Engineering
2011 - 2015
Earned a bachelor's degree in Biological System Engineering with coursework in engineering principles and quantitative analysis applied to biological systems.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
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