Jessica Yung is a research engineer at DeepMind with 11 years of experience blending machine learning research, engineering and product-oriented work across top labs and industry. She helped develop and open-source impactful computer vision models and datasets at Google Brain (co-authoring BiT and MLP-Mixer and releasing SI-SCORE), and now applies that expertise to scalable research engineering at DeepMind. Her background spans startups and founding roles—co-founding CQ2 to automate vulnerability patching and creating Hello Motions, a high-traffic debating motions platform—demonstrating an ability to ship production systems from prototype to users. She also scouts for early-stage founders at Backed VC, bringing technical discernment to venture sourcing and community building. Trained at Cambridge and UCL with nanodegrees in ML and self-driving systems, she combines rigorous academic grounding with hands-on ML engineering across cloud and production stacks. Colleagues would note her unusual mix of research depth, product intuition and a track record of open-source releases that advance model robustness and transfer learning.
11 years of coding experience
3 years of employment as a software developer
Machine Learning Engineer Nanodegree, Machine Learning, Data Analysis, Machine Learning Engineer Nanodegree, Machine Learning, Data Analysis at Udacity
University College London
Bachelor of Arts - BA, Engineering, Economics, Mathematics, First Class Honours, Bachelor of Arts - BA, Engineering, Economics, Mathematics, First Class Honours at University of Cambridge
Mathematics, Physics, and Economics, Year 12-13, Mathematics, Physics, and Economics, Year 12-13 at Westminster School
Mathematics (M2), Physics, English Language and Literature, Chinese, Liberal Studies, HK Secondary 1-4 (UK Years 8-11), Mathematics (M2), Physics, English Language and Literature, Chinese, Liberal Studies, HK Secondary 1-4 (UK Years 8-11) at Diocesan Girls' School
Contributions:9 commits, 188 pushes, 1 branch in 1 year 1 month
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