Daniel Lok
Software Engineer at Databricks
Singapore
Summary
🤩
Rockstar🎓
Top SchoolDaniel Lok is a software engineer based in Singapore with two years of industry experience and a track record of shipping production features at scale across Meta, Dropbox, and Databricks. He has driven measurable product improvements—from a 20%+ lift in browser autofill classification at Dropbox to reliability and performance gains in Meta’s advertiser onboarding—and has led small teams to expand support product reach and reduce churn. Currently contributing to MLflow at Databricks, he blends back-end and DevOps work with practical ML tooling experience, including improving model serialization and gateway configuration documentation. Comfortable across front-end, payments, and machine-learning pipelines, he pairs hands-on coding with a keen eye for UX and operational quality. An early adopter of functional front-end tooling and open-source collaboration, he brings both product-minded engineering and a habit of shipping clean, well-documented solutions.
2 years of coding experience
4 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Yale-NUS College
Github Skills (6)
python10
apidoc9
api9
onnx8
langchain7
documentation6
Programming languages (8)
Github contributions (5)
mlflow/mlflow
Oct 2023 - Jun 2026
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:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:10 releases, 1769 reviews, 929 PRs in 2 years 7 months
Contributions summary:Daniel contributed to the project by implementing a gateway dependency and adding more helpful error messages for saving unserializable LangChain models, which demonstrates an involvement in code functionality. They also set up OpenAI API keys within the code and added a parameter to enable/disable saving ONNX models as external data. They also added a link to the Gateway configuration details in the Quickstart guide, demonstrating an understanding of project documentation.
aimlflowmlmodelmachine-learningml
daniellok-db/mlflow
Oct 2023 - May 2026
Open source platform for the machine learning lifecycle
Contributions:2 PRs, 1345 pushes, 549 branches in 2 years 6 months
machine-learning
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