Software Engineer · AI & infrastructure · Toronto, Canada
I build generative AI that ships, on infrastructure that holds.
I’m Hantang Li (李汉唐). I’ve built GenAI products as an early engineer at a Techstars-backed startup, done computer vision research at the University of Toronto, and most recently worked on large-scale distributed infrastructure at AWS. AI is where my curiosity lives: I follow the frontier closely, and right now I’m studying how models work on the inside.
On a three-month plan: studying mechanistic interpretability and looking for my next role in AI.
Selected work
All projects →Content and layout control for generative systems
A granted US patent on controlling both content and layout when generating marketing visuals with generative models. The system I built during my MScAC internship at Ecomtent later became part of it.
Generative AI for product listings and infographics
Designed and built the ML system behind Ecomtent’s AI-generated product images and infographics: diffusion models for imagery, layout-generation networks with constraints on position and size, and stateless API endpoints on AWS.
MLaaS 6.5k-GPU trace analysis
Analyzed scheduling fairness in a 6.5k-GPU production cluster trace. Finding: wait times on low-end, shared GPUs are distributed more fairly than on high-end ones.
Music-score object detection
Applied a Detection Transformer to dense music-notation detection and surpassed the Faster R-CNN baseline.
Experience
Full resume →- 004Feb 2025 – Oct 2026
Software Development Engineer · Amazon Web Services
Large-scale distributed infrastructure, plus LLM tooling for engineering operations.
- 003May 2023 – Dec 2023
Artificial Intelligence Engineer · Ecomtent (now Azoma)
GenAI SaaS that generates e-commerce product imagery, built on fine-tuned diffusion models.
- 002May 2021 – Jul 2022
Research Assistant · Sunnybrook Health Sciences Centre
Deep learning for stroke imaging: CT perfusion synthesis and lesion segmentation.
- 001May 2020 – May 2021
Research Engineer · Huawei Noah’s Ark Lab
Video classification models trained on large, long-tailed multimodal data.
Writing
All posts →First posts are on the way. Subscribe via RSS to get them when they land.
Let’s talk.
I’m open to new opportunities in AI: applied AI engineering, interpretability, and the infrastructure around them. If you’re hiring, or just want to compare notes, email is the fastest way to reach me.