Dina Jones
Staff AI Software Engineer at Confidential Core AI
Portland, Oregon, United States
Summary
🤩
Rockstar🎓
Top SchoolDina Jones is a Staff AI Software Engineer based in Portland with 10 years of experience building and shipping AI frameworks, distributed training tooling, and production ML systems. She led cross-functional efforts at Intel to produce reference models, transfer-learning tooling, and multimodal RAG chatbots—authoring RFCs, demos, and published blog posts while delivering on schedule. Her hands-on work spans fine-tuning Llama-family models with QLoRA-style methods, multi-agent DPO prototypes, and optimizing workloads for Intel Gaudi and Xeon hardware. An active open-source contributor, she improved time-series tooling on Apache Spark and helped harden Intel’s AI reference models and benchmarking scripts for reproducible deployment. Known for bridging research and engineering, she combines systems-level design (Kubernetes, Slurm, Docker) with pragmatic developer UX improvements and cross-geo coordination. Outside the obvious, she has a track record of turning internal architectures into consumable open-source tools that accelerate others’ ML workflows.
10 years of coding experience
22 years of employment as a software developer
BS, Computer Science, Integrated Media, Mathematics, BS, Computer Science, Integrated Media, Mathematics at Pacific University
Github Skills (21)
apache-spark10
python10
machine-learning10
time-series10
bash10
scala10
vector-autoregression10
deep-learning10
tensorflow10
autoregressive-models10
data-analysis10
breeze9
dockers9
linear-regression9
docker9
Programming languages (7)
Github contributions (5)
intel/ai-reference-models
Oct 2018 - Jun 2022
Intel® AI Reference Models: contains Intel optimizations for running deep learning workloads on Intel® Xeon® Scalable processors and Intel® Data Center GPUs
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:2 releases, 1 review, 585 commits in 3 years 7 months
Contributions summary:Dina contributed to the Intel AI Reference Models repository by adding common scripts, fixing typos, and integrating new features like adding a specific model to an object detection use case. Their work involved modifying Python scripts related to benchmarking, and configuration and also creating and modifying bash scripts for managing the build process and running inference. Furthermore, the commits demonstrate experience in managing the test/build tools by configuring them.
optimizationsprocessorstensorflowzoomodel-zoo
sryza/spark-timeseries
Feb 2016 - Sep 2016
A library for time series analysis on Apache Spark
Role in this project:Back-end Developer
Back-end DeveloperContributions:7 commits, 4 PRs, 5 comments in 7 months
Contributions summary:Dina primarily focused on implementing and refining the `AutoregressionX` model within the `spark-timeseries` library. Their contributions include adding new functionality to the model such as fixing the `predict()` function, incorporating an intercept, and addressing feedback. The user also made updates to the `Lag` utility for time series analysis, and performed code updates. Finally, the user marked relevant classes as serializable.
time-series-analysisapachesparkscalaapache-spark
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