Jared Nielsen
Computer Scientist
Palo Alto, California, United States
Summary
👤
Senior🎓
Top SchoolJared Nielsen is a computer scientist and applied mathematician with nine years of experience building and scaling machine learning systems, from real-time vision pipelines to multi-thousand-GPU distributed training. At AWS he set a time-to-train world record for a 3B-parameter T5 model, open-sourced efficient ALBERT implementations, and launched SageMaker Debugger while maintaining custom deep learning forks used in production containers. He contributes to flagship open-source projects such as Hugging Face’s Transformers and Datasets—adding model fixes, TF-specific enhancements, dataset sharding, and TFRecord export support—bridging research and production tooling. His background spans NLP, computer vision, and reinforcement learning, with practical wins in realtime product classification, signal-based predictive maintenance, and frequency-domain medical imaging. Based in Palo Alto, he pairs rigorous academic training (BYU and Georgia Tech) with an engineer’s focus on measurable system impact and reproducible ML workflows. An under-the-radar strength is his track record of shipping both novel research and robust engineering—open-sourcing research code that became production-grade infrastructure.
9 years of coding experience
5 years of employment as a software developer
Master's degree, Computer Science, Master's degree, Computer Science at Georgia Institute of TechnologyBachelor's degree, Computational and Applied Mathematics, Bachelor's degree, Computational and Applied Mathematics at Brigham Young University
English, Danish
Stackoverflow
3,827reputation
848kreached
22answers
31questions
java
top-5%
Github Skills (26)
transformers10
python10
machine-learning10
datasets10
deep-learning10
tensorflow10
bert10
nlp10
pyarrow9
hub9
pytorch9
data-pipelines9
java9
9
numpy9
Programming languages (10)
Github contributions (5)
huggingface/transformers
Jan 2020 - Aug 2020
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Role in this project:
ML Engineer
ML EngineerContributions:9 commits, 17 PRs, 28 comments in 6 months
Contributions summary:Jared's contributions primarily focus on improving the code related to the `transformers` library's machine learning capabilities. They've fixed a `KeyError` in a script, added functionality to a SQuAD-related data processing pipeline, corrected dropout probabilities in an ALBERT model implementation, and adjusted TensorFlow-specific docstrings. Further contributions include the addition of new pre-training models and fixing dropout layers for various transformer models.
pythonbertspeech-recognitionstate-of-the-artflax
huggingface/datasets
Jul 2020 - Jul 2020
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Role in this project:ML Engineer & Data Engineer
ML Engineer & Data EngineerContributions:7 commits, 7 PRs, 32 comments in 20 days
Contributions summary:Jared significantly contributed to the `huggingface/datasets` repository by implementing new functionalities for dataset manipulation and export. Their work includes adding a `shard()` method for dataset partitioning, allowing for flexible dataset splitting and contiguous sharding. They also developed a feature to export datasets to TFRecords format, demonstrating proficiency in data serialization for machine learning tasks and integrating datasets with TensorFlow. The user's contributions extend to adding new datasets, such as a text dataset, and providing the necessary tools for dataset handling.
ml-modelstensorflownatural-language-processingmanipulationdata-science
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