Siddharth Murching
Summary
🤩
RockstarSiddharth Murching is a Software Engineer based in San Francisco with 12 years of experience and a Caltech CS background, currently building ML infrastructure at Databricks since 2017. He specializes in bridging machine-learning frameworks and big-data systems—contributing to high-profile open-source projects like MLflow and spark-sklearn and adding Keras model support to Spark deep-learning pipelines. His work spans backend and DevOps responsibilities: CI/CD, dependency and version management, build/test reliability, and Databricks-specific project execution and DBFS integration. Notably, he’s kept deprecated but widely used tooling usable and stable across Python, TensorFlow, and scikit-learn version changes, demonstrating an eye for long-term maintainability.
12 years of coding experience
Stackoverflow
486reputation
45kreached
6answers
0questions
Github Skills (40)
apache-spark10
dockerce10
docker10
data-pipelines10
python10
back-end-development10
scikit10
databricks10
mlflow10
dockers10
scala210
scala10
keras10
tensorflow210
deep-learning10
Programming languages (13)
Github contributions (5)
databricks/spark-sklearn
Sep 2017 - Sep 2017
(Deprecated) Scikit-learn integration package for Apache Spark
Role in this project:
ML Engineer
ML EngineerContributions:44 commits, 11 PRs, 2 pushes in 23 days
Contributions summary:Siddharth primarily contributed to the `spark-sklearn` project by addressing version requirements and fixing doctests. They consistently updated the project's dependency on scikit-learn, ensuring compatibility and stability. Their work involved modifications to the `setup.py` file and core files related to GridSearchCV, improving the integration of scikit-learn with Apache Spark.
spark-mlapachesparkscikit-learnscala
mlflow/mlflow
Jun 2018 - Aug 2022
Open source platform for the machine learning lifecycle
Role in this project:Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:13 releases, 656 reviews, 318 commits in 4 years 3 months
Contributions summary:Siddharth primarily contributed to Databricks-related project execution, implementing and refining features for running MLflow projects on Databricks clusters. Their contributions included updates to documentation, improvements to the core project execution logic, and enhancements related to the Databricks environment, specifically including uploading projects to DBFS, and managing authentication variables and supporting both local and cloud setups. They also worked on testing and improved build steps for the Java package.
pythonlifecyclemlmachine-learningincremental-learning
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.