Jane Liang
Engineer at UpHonest Capital
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolJane Liang is an engineer in the San Francisco Bay Area with a decade of experience building production AI systems and full-stack products. She has shipped scalable ML and inference services at Amazon (Alexa) and optimized generative AI infrastructure and candidate-facing products at startups like Dover and Valon, balancing product thinking with backend performance work. At Dover she scaled AI pipelines 10x without throughput loss and helped grow the engineering team through hiring and mentoring, and she later contributed to stealth and early-stage ventures before joining Alma. Jane combines academic robotics and vision research from UC Berkeley with hands-on deployment experience, making her comfortable both in model training and in operating real-time services. Outside core engineering she scouts startups for UpHonest Capital, signaling a nose for product-market fit and emerging AI trends.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Science - BS, Electrical Engineering and Computer Science, Bachelor of Science - BS, Electrical Engineering and Computer Science at University of California, Berkeley
English, Chinese, Korean, Spanish
Github Skills (11)
simulations4
simulation4
python3
physics3
mujoco2
nodejs2
aws2
physics-engine2
amazon2
api2
cpp2
Programming languages (3)
Github contributions (5)
yishuangl/page
Oct 2015 - Jun 2022
Contributions:66 pushes, 1 branch in 6 years 9 months
yishuangl/cal
Nov 2015 - Jan 2016
Contributions:13 pushes, 1 branch in 2 months
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