Marco Montagna
Member Of Technical Staff at Perplexity
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMarco Montagna is a seasoned software engineer with 11 years of experience building and scaling data-intensive systems and distributed services from startups to major platforms in the Bay Area. He has progressed through senior engineering roles at Instacart to Principal and now serves as Member of Technical Staff at Perplexity, combining hands-on development with system-wide reliability and cost-optimization efforts. His background spans backend, database engineering, ETL and ML infra—evidenced by migrating multi-terabyte databases, cutting infrastructure costs, and contributing to Instacart’s lore ML framework and the widely used activerecord-multi-tenant project. Marco excels at bridging research and production: he’s implemented sensor-data pipelines ingesting hundreds of millions of points per day, built ad-intelligence ETL at scale, and dogfooded deployment/tooling improvements that materially reduced bills. Comfortable across Python, Ruby/Rails, Docker/ECS and cloud databases, he looks for consulting opportunities where pragmatic architecture and measurable operational wins matter. He brings a pragmatic scientist’s mindset from his UC Berkeley CS background, often translating experimental code into robust production systems.
11 years of coding experience
10 years of employment as a software developer
Bachelor’s Degree Computer Science, Bachelor’s Degree Computer Science at University of California, Berkeley
English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (15)
activerecord10
pandas10
ruby-rails10
machine-learning10
rails10
postgresql10
sql10
python10
multi-tenant10
devops9
ruby9
aws-s38
s3-bucket8
amazon-s38
tensorflow7
Programming languages (9)
Github contributions (5)
instacart/lore
Jan 2020 - Feb 2020
Lore makes machine learning approachable for Software Engineers and maintainable for Machine Learning Researchers
Role in this project:
ML Engineer & DevOps Engineer
ML Engineer & DevOps EngineerContributions:35 commits, 15 PRs, 25 pushes in 8 days
Contributions summary:Marco primarily contributed to the development and maintenance of the `lore` machine learning framework. Their work included modifying the `io` module for improved data loading, fixing a geo IP test, and refactoring the code for Python 3 compatibility. They also added a script for releasing new versions and addressed a bug related to S3 bucket handling. This indicates a focus on both model development and deployment infrastructure.
pythondata-sciencemachine-learningresearchersgluon
citusdata/activerecord-multi-tenant
Aug 2022 - Aug 2022
Rails/ActiveRecord support for distributed multi-tenant databases like Postgres+Citus
Role in this project:Back-end Developer / Database Engineer
Back-end Developer / Database EngineerContributions:6 commits, 4 PRs, 7 comments in 2 days
Contributions summary:Marco primarily contributed to bug fixes and enhancements within the `activerecord-multi-tenant` project. Their work focused on refining query building logic, particularly addressing issues related to mismatched partition keys and ensuring correct SQL generation for multi-tenant database environments. The user also worked on fixing tests, including those for models with nonstandard class names. Their contributions improved the reliability and correctness of the library's ActiveRecord integration.
tenantrailscitusrubymulti-tenant
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