Arpit Jasapara is a software engineer in San Francisco with 4 years of experience focused on backend systems and MLOps at Databricks. He is an active contributor to the widely used MLflow project, where he improved tracking-server stability by implementing SQLAlchemy engine caching to prevent connection leaks and added Databricks-specific git metadata integrations that link code versioning to run and model registry workflows. His background includes internships at Google, LinkedIn, Affirm, and Oath, demonstrating experience shipping reliable infrastructure at scale. He holds both a BS and an MS from UCLA and combines practical model-management expertise with production-grade backend engineering.
Open source platform for the machine learning lifecycle
Role in this project:
Back-end Developer & MLOps Engineer
Contributions:96 reviews, 4 commits, 41 PRs in 1 year
Contributions summary:Arpit primarily focused on improving the stability and efficiency of the MLflow tracking server's back-end components. They addressed database connection management issues, specifically optimizing SQLAlchemy engine usage by implementing engine caching to prevent resource leaks. They also contributed to the integration of Databricks-specific functionalities related to git repository metadata, demonstrating an understanding of MLOps practices by connecting code versioning with run tracking. Additionally, the user worked on Model Registry features, demonstrating knowledge of model management.
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