2024 - present
BambooHR
Staff AI/ML Engineer
Leading AI platform work for Ask BambooHR and shared production agent infrastructure: durable runtimes, tracing, observability, evals, and reliable tool use.
Joe Davison
I've been doing machine learning since 2015. Most of the work I'm proudest of has been in NLP: zero-shot classifiers, open-source Transformers tooling at Hugging Face, and later ML for molecular structure and drug discovery at Enveda.
Timeline
A compact version of the path so far.
2023 - 2024
University of Utah
Doctoral studies in computing and AI
Spent a year in doctoral studies with Vivek Srikumar, focusing on NLP, machine learning, and language-model research. Ultimately decided a PhD wasn't the right path for me, so I left.
2021 - 2022
Enveda Biosciences
Senior Machine Learning Scientist
Built Transformer training infrastructure and sequence-to-structure models for molecular identification from noisy MS/MS spectra.
2020 - 2021
Hugging Face
Research Engineer, Science Team
Worked on Transformers and Datasets, zero-shot classification tooling, public models, demos, and research infrastructure.
2018 - 2020
Harvard
MS Data Science
Studied data science at Harvard and interned at IBM Research / MIT-IBM Watson AI Lab, working on cross-population variational autoencoders for isolating latent structure across distributions.
2015 - 2018
BYU
BS Computer Science
Studied computer science at BYU, interned at Microsoft on CNTK, and built early machine-learning projects including MMLSpark NLP components, get_smarties, and devol.
Writing
2020, Blog post
Zero-Shot Learning in Modern NLP
Practical methods for text classification without annotated data; cited in academic literature.
2020, Blog post
REALM: Knowledge and Transformers
Notes on retrieval-augmented language model pretraining.
2020, Hugging Face Docs
Perplexity of fixed-length models
Reference guide for evaluating causal language models with fixed context windows.
2020, Reading group write-up
Attacking Bert: Weight Poisoning Attacks on Pre-Trained Models
Hugging Face reading group discussion and Colab notes on poisoned pretrained model weights.
2021, X/Twitter
Introductory explainer thread on prompting
A 2021 thread on prompt-based language model use, written before RLHF-tuned chat models popularized the interface.
2018, Medium
Publications
Selected papers. Citation counts are intentionally approximate; see Google Scholar for the changing record.
2019
2019
2020
Transformers: State-of-the-Art Natural Language Processing
EMNLP Demo
Best Demo Award; 14,000+ citations
2021
Datasets: A Community Library for Natural Language Processing
EMNLP Demo
Best Demo Award; 900+ citations
2023
MS2Mol: A Transformer Model for Illuminating Dark Chemical Space from Mass Spectra
ChemRxiv
35+ citations
2022
Multi-scale sinusoidal embeddings enable learning on high resolution mass spectrometry data
ICLR 2023 MLDD Workshop Oral
7 citations
Misc.
Useful projects, demos, and models that do not fit cleanly into papers or writing.
2026, Open source
Alien Physics Lab
Small RLVR-style playground for training agents to run experiments, reason from noisy measurements, and recover hidden physical parameters with verifiable rewards.
2026, Open source
Sparse decode experiments & kernels
Training-free sparse attention and KV-cache routing experiments for long-context LLM decode, including a from-scratch Triton kernel and documented negative results.
2024, Recognition
AI Utah 100
Named to the inaugural AI Utah 100 list as a Builder.
2025, Patent
Patent US20250189496A1
Patent publication related to mass-spectrometry-based molecular structure prediction.
2021, Podcast guest
Deriving value from NLP and Transformers
AI & U episode on NLP, Transformers, and semantic understanding.
2020, Open source
Zero-shot classification pipeline
Transformers pipeline and task workflow for classifying text against arbitrary candidate labels.
2021, Open source
Zero-shot distillation
Self-distillation project for training smaller zero-shot classifiers from larger NLI models.
2020, Models
Custom NLI and zero shot models
Public zero-shot and student classifiers on the Hugging Face Hub, including BART, XLM-R, and DistilBERT models.
2020, Demo
Zero-shot classification demo
Interactive Hugging Face Space for classifying text with arbitrary labels.
2017, Open source
DEvol
Early proof of concept for genetic neural architecture search.