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Yi-Chin Wu's Personal Email and Phone Number
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Yi-Chin Wu
Manager of Machine Learning
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Location: Mountain View, California, United StatesApprox. Years of Experience: 16
Yi-Chin Wu's Current Workplace
Pinterest
Company Size
2500+
Amount Raised
$1.5B
Pinterest's mission is to bring everyone the inspiration to create a life they love. It’s the biggest dataset of ideas ever assembled, with over 200 billion recipes, home hacks, style inspiration and other ideas to try. More than 430 million people around the world use Pinterest to dream about, plan and prepare for things they want to do in life.
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Notable Investors
Andreessen Horowitz, FirstMark, Fidelity, Wellington Management, Acequia Capital (AceCap)
Social Media
Photo Sharing
Social Network
Content Discovery
Experience
Manager of Machine Learning
Pinterest
Jun 2025 - Present
2 mos
Search retrieval
Career Break
Mar 2025 - May 2025
3 mos
- Family, recharged and refocused - GenAI side projects: A web-based journaling application powered by RAG, enabling users to create a personalized AI companion tailored to their unique journaling needs. Hosted for friends and family. Stack includes: LangChain, OpenAI API, Supabase, Streamlit / Next.js, FastAPI
Machine Learning Engineer
Roblox
Jun 2023 - Mar 2025
1 yr 10 mos
Roblox omnisearch team - Designed and implemented Roblox’s first game search ML ranker. Contributed to semantic search retrievals, token-based retrievals, and vertical classification efforts. Drove +X% game search deep conversion rate and +X% relevance - Contributed to Roblox's PyTorch-based ML libraries and unblock text feature adoption across Discovery. - Partnered with cross-functional teams to define search shipping criteria and establish robust evaluation practices.
Twitter
Jul 2019 - Feb 2023
ML Engineering Manager - Recommendation Systems (Twitter 2.0 / X)
Nov 2022 - Feb 2023
4 mos
ML Platform Signal Relevance - Leading a team of MLEs and researchers focusing on: user interests embedding, content understanding embedding, and embedding-based candidate retrieval for multiple product verticals (Home, Notifications, Ads, Search, Health)
ML Engineering Manager - Recommendation Systems
Jul 2021 - Oct 2022
1 yr 4 mos
Recommendations Platform Representations - Led a horizontal team focused on building unified, interest-based representations for various Twitter entities to power personalized recommendations across multiple product verticals. - Drove +X% User Active Minutes and +X% Daily Active Users - Leveraged techniques from Neural network, GraphML, big data processing - Built and grew to a team of 12 MLEs across US and UK. - Collaborated cross-functionally with research and product teams to align modeling improvements with business goals and user experience enhancements.
Machine Learning Engineer
Jul 2019 - Jun 2021
2 yrs
Recommendation systems for consumer products - Two-tower model-based tweet similarity - Topic tweets recommendation
Pure Storage
May 2016 - Jul 2019
Senior Software Engineer - Machine Learning
Mar 2019 - Jul 2019
5 mos
Software Engineer - Machine Learning
May 2017 - Mar 2019
1 yr 11 mos
Pure1 Meta Workload Planner: We utilize machine learning to develop a planning tool that allows customers to predict their storage array loads, with different hardware configuration or workload allocation. This features marks as the #1 page views on Pure1 (Pure Storage's cloud-based management tool) besides the landing page. - Model research (data cleaning, model design/selection/validation, hyperparameter tuning) and define machine learning metrics to hit the product goals. - Researched and utilized machine learning models such as random forest, gradient boosting, KNN, MLP, LSTM, etc. - Implemented ETL pipelines in Spark to extract features and reference data. - Productionize models in REST servers. - Designed and the implemented automated testing/experiment pipelines to speed-up model research. - Lead the effort to help the data generation team to produce cleaner data. - Interact with sales engineers and customers to understand product requirements and expectations. Leadership: - Co-founded study group within the Pure1 business organization. This is a recurring event that allows engineers and PMs to learn from others through hands-on labs. - Co-hosted super lightning talks events in which teams pitched their projects in 10 slides and 3 min 20 sec. Award: - Archimedes Cup (Pure1 best individual of the quarter), award to one of 150+ employees within Pure1 business organization - Hackathon Creativity Award Pure1 META: Pure’s AI Platform to enable Self-Driving Storage
Software Engineer
May 2016 - May 2017
1 yr 1 mo
Cloud-Connector project: Drove and implemented in Java a new log uploading module that replaced the legacy system. The new log uploader utilized in-memory databases to improve efficiency and robustness. Contributed to the design for modularization and multi-device support.
Postdoctoral Researcher
TerraSwarm Research Center
Sep 2014 - May 2016
1 yr 9 mos
Combined formal methodologies and control theory in controlling privacy. Developed algorithms that ensure privacy while preserving output utility. Implemented a Python toolkit that utilized BDD-based formal verification techniques. EdiSyn, a toolkit for synthesizing obfuscators that enforce privacy while preserving utility
University of Michigan
Jan 2010 - Aug 2014
Graduate Student Research Assistant
2009 - Aug 2014
5 yrs 8 mos
• Investigated opacity, a formal privacy notion, for various formulations of private behaviors and developed algorithms verifying whether opacity is satisfied. • Studied opacity enforcement by obfuscating the output data. Developed algorithms generating obfuscators that guarantee opacity. Investigated the proposed obfuscation-based enforcement mechanism under different attack models and different performance criteria. • Investigated intrusion detection rules for networked control systems in the presence of vulnerable actuators. Developed algorithms detecting attacks and identified conditions when attacks can be detected. • Investigated non-blocking properties of automotive Passive Entry and Keyless Go (PEKG) system. Constructed formal models for PEKG system from the C source codes and developed C++ analysis tools. The proposed approach identified blocking states caused by a typographical error. VEiP, a toolkit for opacity verification and enforcement in Discrete Event Systems
Graduate Student Instructor - EECS 501. Probability and Random Processes
Sep 2010 - Dec 2011
1 yr 4 mos
Led weekly discussion sessions, discussed with instructors to develop course materials and quizzes, and evaluated students through grading.
Graduate Student Instructor - EECS 460. Control Systems Design and Analysis
Jan 2010 - Apr 2010
4 mos
Led weekly discussions, and guided students in a magnetic levitation project where they designed PID controllers that levitate a metallic ball by utilizing Matlab and Simulink.
Praktikum (Intern)
Industrial Automation Division, Siemens AG
May 2012 - Aug 2012
4 mos
Implemented network intrusion detection with Snort, reversed-engineered malicious logs with Wireshark, and conducted penetration tests. The implementation and analysis identified real network threats.
Engineering Teaching Consultant
Center for Research on Learning and Teaching, University of Michigan
Sep 2011 - Dec 2011
4 mos
Provided teaching consultation services for Graduate Student Instructors (GSIs) and Instructional Aides (IAs) in the College of Engineering.
Intern
Ford Motor Company
Jul 2009 - Aug 2009
2 mos
Investigated driver drowsiness using eye movement data. Analyzed the correlation between different types of eye movements using Matlab.
Education
  • Dates unavailable
    National Taiwan UniversityBachelor of Science, Electrical Engineering
  • Dates unavailable
    University of MichiganPhD, EE:System