Dillon Hicks
Machine Learning Engineer at Atlassian
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolDillon Hicks is a Machine Learning Engineer based in San Francisco with 8 years of hands-on experience building production ML and deep learning systems across industry and research. He holds an MS in Machine Learning and Data Science from UC San Diego and has delivered end-to-end solutions from AWS-based ETL and document processing pipelines to NVIDIA edge deployments and real-time signal classification. Dillon has driven measurable impact—cutting manual data entry by over 90%, speeding analyst queries from 20+ minutes to under 30 seconds with agentic RAG systems, and achieving 95% geospatial segmentation accuracy used to inform government carbon policies. His background blends academic rigor at NASA Ames and UCSD with practical startup and enterprise deployments at Trilogy and Atlassian, including transformer-based modeling, ONNX edge inference, and reproducible ML workflows (MLflow, DVC). He’s comfortable orchestrating multi-agent LLM pipelines and integrating cutting-edge models like Llama 3 and Claude into production, and he brings an appetite for “anything and everything” experimentation that fuels rapid prototyping and impactful ML products.
8 years of coding experience
4 years of employment as a software developer
University of California, San Diego
Github Skills (6)
machine-learning5
dvc4
deep-learning4
monitoring4
incremental-learning4
data-science4
Programming languages (5)
Github contributions (5)
UCSD-E4E/ml-mangrove
Jun 2020 - May 2022
Machine Learning Development and code for the Mangrove Monitoring Project
Contributions:52 commits, 2 PRs, 50 pushes in 1 year 11 months
mangrovedata-sciencedeep-learningmachine-learninglearning-and-development
UCSD-E4E/mangrove
Jun 2018 - Aug 2020
Repo for storing the code and tools for the mangrove conservation project
Contributions:118 commits, 1 PR, 107 pushes in 2 years 2 months
storingmangroveconservation
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