Avesh Singh
Senior Software Engineer at Databricks
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAvesh Singh is a Senior Software Engineer in San Francisco with nine years of experience building scalable ML and search systems at Databricks, Cardiogram, and Google. He led ML infrastructure and feature store work, previously directing model training pipelines that processed petabytes of data and converted 5TB of Postgres into TensorFlow-ready inputs at Cardiogram, helping produce published medical ML research. At Google he improved search-ranking signals and retooled an orphaned web corpus job from multi-day to hourly runs, demonstrating a knack for performance optimization and cross-team collaboration. An active contributor to MLflow, he has practical experience with model deployment (including SageMaker and Unity Catalog) and improving developer UX through docs and utilities. Colleagues describe him as a builder who prefers becoming—continually iterating on systems and skills rather than resting on past achievements.
10 years of coding experience
6 years of employment as a software developer
Moorestown High SchoolBachelor of Science, Computer Science, Bachelor of Science, Computer Science at Carnegie Mellon University
Stackoverflow
11reputation
322reached
1answer
1question
Github Skills (15)
machine-learning10
model-management10
mlflow10
python10
documentation9
sagemaker9
sql8
yaml7
heroku6
apache-spark6
ai6
postgresql6
dockers5
model-registry5
docker5
Programming languages (4)
Github contributions (5)
mlflow/mlflow
Jan 2020 - Dec 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:
ML Engineer
ML EngineerContributions:1 release, 72 reviews, 21 commits in 1 year 10 months
Contributions summary:Avesh primarily contributed to the documentation and functionality of the MLflow platform. Their work included adding examples for querying the best models using the search API, improving page titles for a more descriptive user experience, and updating release notes. Additionally, the user made changes to support SageMaker model deployment and updated the code for Unity Catalog model registry. They also addressed package dependencies and made improvements to file utilities.
aimlflowmlmodelmachine-learningml
AveshCSingh/mlflow
Jan 2020 - Feb 2026
Open source platform for the machine learning lifecycle
Contributions:137 pushes, 42 branches in 6 years 1 month
pythonlifecyclemachine-learningmlops-workflowmodel-management
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