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Jason Liu

ML Engineer, Consultant, Advisor

[email protected] | jxnl.co | jxnl | jxnlco

Executive Summary

I'm a former Staff MLE who built a 7-figure AI business by bridging the gap between research, product, and customers. I created Instructor (3M+ monthly downloads) and have spent 10+ years building AI systems at scale while training 1000+ practitioners. I help companies establish thought leadership in agent engineering, build evaluation frameworks from customer insights, and drive developer adoption at scale. I'm looking for my next 4-5 year project to apply this expertise.

Professional Experience

Founder, 567 Studio

2023 - Present

  • Work with Seed to Series B companies, helping engineering teams adopt AI best practices and upgrade existing LLM systems to agentic applications across Retrieval Augmented Generation (RAG), Context Engineering, and Evals.
  • AI consulting for Distributional, Galileo, Zapier, HubSpot, Limitless, Tensorlake, Trunk Tools, New Computer, Weights & Biases, Modal Labs, Timescale, and others across construction, medical, CRM, and personal assistant industries
  • Built training programs on improving AI systems on Maven serving professionals from OpenAI, Anthropic, Google, Microsoft, Amazon, Netflix
  • Designed workflow automations, fine-tuned embedding models for images/diagrams/videos across industries (consulting, oil & gas, meeting notes, red teaming, medical, crm, personal assistants)
  • Conducted AI adoption training for enterprise CTOs and engineering teams, establishing monthly lunch-and-learn programs and best practices frameworks

Staff Machine Learning Engineer, Stitch Fix

2018 - 2023

  • Architected multimodal embedding similarity system using ResNet-50 transfer learning and CLIP+GPT-3 integration generating $50M+ annual revenue impact
  • Designed Flight framework handling 350M+ daily requests with 80% internal adoption rate across engineering teams
  • Built styling chatbots using DaVinci chat models, integrating LLMs for stylist workflows and improving recommendation quality by 40%
  • Technical lead for team of 6-7 engineers and data scientists

Side Projects

  • Instructor Python library (4.5M+ monthly downloads), recognized and referenced by OpenAI. Technical documentation, API design, and developer onboarding experiences.
  • Data Science Arena system for training AI judges on analysis quality, enabling preference collection and evaluation beyond code correctness

Data Scientist, Facebook (Meta) - Protect & Care

2017

  • Developed ML algorithms detecting harmful content (violence, hate speech, child endangerment) with 95%+ accuracy at 2B+ user scale
  • Built real-time monitoring dashboards identifying malicious activities, reducing escalation time by 50%
  • Contributed to platform integrity improvements protecting global user base

Education

Bachelor of Mathematics in Computational Mathematics & Statistics

University of Waterloo, Ontario, Canada | 2012-2017

Background: Mathematical physics and computational statistics before transitioning to applied machine learning

Publications & Research

Liu, J., Weitzman, E.R., & Chunara, R. (2017). Assessing behavior stage progression from social media data. Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, 1320–1333.

Rehman, N., Liu, J., & Chunara, R. (2016). Propensity score matching for vaccination sentiment analysis. AAAI Spring Symposium on Observational Studies through Social Media and Other Human-Generated Content, 23–25.


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