Rick Battle
Staff Machine Learning Engineer at VMware
Earth, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolRick Battle is a Staff Machine Learning Engineer with 14 years of experience building and operationalizing NLP and deep learning systems, currently leading VMware’s R&D AI Lab (RAIL) and custom language-modeling efforts in partnership with Stanford DAWN Lab. He has a strong track record of taking research into production—bringing VMware-specific models like vBERT and vNLP into service—and mentors teams through internal competitions, workshops, and internship programs. His background blends hands-on ML engineering (Transformers, PyTorch, TensorFlow) with full-stack deployment experience and infrastructure design for rapid model rollout. A former naval communications systems engineer and project lead, he pairs disciplined systems thinking and large-team leadership with practical ML research. He is also an active contributor to open-source ML tooling, having enhanced DSPy integrations for Hugging Face models, multi-GPU inference, and causal LM support.
14 years of coding experience
4 years of employment as a software developer
Virginia TechMaster of Science - MS, Computer Science, Master of Science - MS, Computer Science at Naval Postgraduate School
c/c++, php, mysql, java, javascript, xhtml, html5, css, c#, bash, cuda, perl, xml, vba, rest, python
Github Skills (10)
transformers10
huggingface-transformers10
transformer10
machine-learning10
nlp10
deep-learning10
dsym10
python10
natural-language-processing10
tokenizer9
Programming languages (2)
Github contributions (5)
stanfordnlp/dspy
Jan 2023 - Apr 2024
DSPy: The framework for programming—not prompting—language models
Role in this project:
ML Engineer
ML EngineerContributions:5 PRs, 19 pushes, 1 branch in 1 year 3 months
Contributions summary:Rick primarily contributed to the integration and enhancement of Hugging Face (HF) models within the DSPy framework. Their work includes fixing examples, adding support for multi-GPU inference, handling JSON parsing errors, and integrating support for Causal Language Models. They also dropped prompts from the output of Causal LMs and added a demo program to showcase the functionality.
language-model
detaos/ColBERT
Jul 2021 - Jul 2023
ColBERT: Contextualized Late Interaction over BERT (SIGIR'20)
Contributions:4 pushes in 1 year 11 months
pytorchnlptransformersinteractionbert
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