Jules Damji
Product Developer Relations -- Staff Developer Advocate
Fremont, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJules Damji is a seasoned distributed-systems and developer-relations leader with 12+ years driving adoption of big data, MLflow, Ray, and Apache Spark across developer and enterprise communities. He blends deep hands-on engineering—Java, Python, Scala, Spark, and backend systems—with a rare communications pedigree (MA in Communication) that powers strategic advocacy, public speaking, and technical storytelling. Jules has led global community growth programs at Anyscale and Databricks, co-chaired major summits, authored Learning Spark (2nd Ed.), and contributed user-facing docs and runnable examples to flagship projects like Ray and MLflow. His background building scalable server infrastructure at ProQuest and earlier systems work at Netscape and Sun grounds his product recommendations in practical production experience. An effective bridge between engineering and product, he embeds with teams to surface developer needs while producing deep technical content, workshops, and trainings. Based in Fremont, CA, he combines open-source stewardship with a knack for turning complex distributed computing problems into accessible developer solutions.
12 years of coding experience
32 years of employment as a software developer
Johns Hopkins UniversityMsc Computer Science, Msc Computer Science at Cal StateBsc Computer Science, Bsc Computer Science at Oregon State University
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (24)
apache-spark10
data-pipelines10
python10
mlflow10
scala10
ray10
data-pipeline10
documentation10
spark-structured-streaming9
pyspark9
streaming9
stream9
data-analysis8
sql8
model-registry7
Programming languages (7)
Github contributions (5)
databricks/LearningSparkV2
Mar 2019 - Apr 2021
This is the github repo for Learning Spark: Lightning-Fast Data Analytics [2nd Edition]
Role in this project:
Data Engineer & Back-end Developer
Data Engineer & Back-end DeveloperContributions:126 commits, 6 PRs, 3 pushes in 2 years 1 month
Contributions summary:Jules contributed code for generating and analyzing M&M data, implementing Python scripts and Scala code for data processing and aggregation. They developed data generation scripts and implemented functionality for counting M&M colors by state, including both Python and Scala versions. The user also added supporting files, including build configurations, and created Databricks notebooks showcasing the chapter examples.
data-analyticssparkapache-sparkstructured-streamingspark-sql
mlflow/mlflow
Jul 2018 - Apr 2021
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
Role in this project:Technical Writer
Technical WriterContributions:142 reviews, 51 commits, 52 PRs in 2 years 9 months
Contributions summary:Jules's contributions primarily involve documentation updates and the addition of code snippets. They have fixed typos and grammatical errors across several documentation files, including those related to tracking, models, and the model registry. The user has also added code examples for various MLflow APIs and model flavors such as fastai, PyTorch, and scikit-learn, improving the documentation for new users. These changes focus on enhancing the clarity and usability of the MLflow documentation.
aimlflowmlmodelmachine-learningml
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