Haibin Lin
Research Scientist & Engineering Leader, Applied Machine Learning at ByteDance
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolHaibin Lin is a research scientist and engineering leader with 12 years of experience building foundation-model infrastructure and large-scale ML systems from the Bay Area. He leads a ~30-person team at ByteDance Seed focused on training infrastructure for search, recommendation, moderation, multi-modal models and LLMs, and has co-authored papers at top systems and ML venues. Previously at AWS he helped optimize MXNet and distributed training stacks, delivered the fastest BERT pre-training in the cloud at the time, and contributed to production NLP toolkits used across Alexa and other services. A prolific open-source contributor, his work spans deep learning frameworks and compilers (MXNet, TVM, DGL, GluonNLP, mshadow) with practical low-level optimizations in sparse ops, memory planning and distributed training. He blends research and engineering: comfortable in compiler-level C++/CUDA fixes as well as RL/LLM training pipelines and MLOps integrations. An uncommon strength is his track record of moving cutting-edge research into robust, production-grade infrastructure that scales.
12 years of coding experience
4 years of employment as a software developer
Overseas Exchange Program, Overseas Exchange Program at University of TorontoThe University of Hong Kong (HKU)Master’s Degree, Master’s Degree at Carnegie Mellon UniversityPreparatory Year Program, Preparatory Year Program at Shanghai Jiao Tong University
Stackoverflow
377reputation
78kreached
18answers
0questions
Github Skills (63)
database10
tvm10
pytorch10
sparse-array10
c-language10
distributed-training10
postgresql10
data-pipelines10
preprocessing10
python10
optimizers10
optim10
preprocess10
memory-management10
gpu-programming10
Programming languages (13)
Github contributions (5)
dmlc/gluon-nlp
Jun 2018 - Aug 2020
NLP made easy
Role in this project:
Full-stack Developer & ML Engineer
Full-stack Developer & ML EngineerContributions:11 releases, 1 review, 151 commits in 2 years 2 months
Contributions summary:Haibin made significant contributions to the `gluon-nlp` repository, demonstrating a strong focus on Natural Language Processing (NLP) tasks. Their work included enhancements to the data stream API, specifically for streaming corpora, by adding support for custom samplers. Furthermore, they were deeply involved in the development of BERT models, including bug fixes, updates, and optimizations. Finally, the user added a pre-training script for BERT using the OpenWebText dataset.
nlpmxnetnatural-language-understandingnlgnatural-language-generation
apache/mxnet
Mar 2016 - Aug 2020
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Role in this project:ML Engineer & Data Scientist
ML Engineer & Data ScientistContributions:3 releases, 239 commits, 721 PRs in 4 years 5 months
Contributions summary:Haibin contributed to the development and enhancement of deep learning models within the MXNet framework. Their work focused on sparse matrix operations and optimization, including improving the performance of the `sparse.dot` operation and integrating multi-precision AdamW updates. The contributions showcase a strong understanding of machine learning algorithms, data structures and their efficient implementation, as evidenced by the optimization efforts. The user was also involved in fixing issues related to the KVStore and its integration within the trainer.
pythonschedulerdataflowmutationdata-science
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