Savin Goyal
Co-Founder & CTO at Outerbounds
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolSavin Goyal is a Co-Founder and CTO with 11 years of experience building ML infrastructure and developer-facing systems, currently leading the engineering vision at Outerbounds from San Francisco. He previously led Machine Learning Infrastructure at Netflix, contributing significantly to Metaflow—an open-source AI/ML platform adopted across Fortune 500 teams—where he improved AWS integrations, CLI usability, and complex decorator parsing. His background spans high-scale ML and data infrastructure roles at LinkedIn and Rocket Fuel, grounding him in both real-time bidding and economic-graph data mining. Comfortable at the intersection of systems, AI and design, he pairs hands-on backend and DevOps expertise with product-minded leadership. An IIT Delhi computer science alumnus with graduate coursework at Stanford, he brings a pragmatic research sensibility (including work in quantum complexity) to building human-centric AI tooling.
11 years of coding experience
9 years of employment as a software developer
Indian Institute of Technology Delhi (IIT Delhi)Graduate Coursework in Statistics & Operations Research, Graduate Coursework in Statistics & Operations Research at Stanford University
Stackoverflow
141reputation
2kreached
4answers
0questions
Github Skills (19)
python10
aws10
aws-step-functions10
aws-batch10
cloud-computing9
command-line-interface9
devops9
command-line9
cli9
s3-bucket8
amazon-s38
configuration-management8
aws-s38
infrastructure-as-code7
dockers7
Programming languages (8)
Github contributions (5)
Netflix/metaflow
Dec 2019 - Jan 2023
Build, Manage and Deploy AI/ML Systems
Role in this project:
Backend & DevOps Engineer
Backend & DevOps EngineerContributions:73 releases, 1073 reviews, 228 commits in 3 years 2 months
Contributions summary:Savin's contributions primarily focused on enhancing the AWS configuration module and improving the usability of the command-line interface for the Metaflow framework. They revamped the AWS configuration module, fixing issues, and adding features like setting up S3 datastores, configuring AWS Batch, and integrating with the AWS Step Functions and IAM roles. Additionally, the user made changes to improve the parsing logic for decorators, enabling more complex arguments to be passed through the CLI. Furthermore, the user contributed to addressing various usability issues in the framework.
pythonml-infrastructureclir-packagescience
Netflix/metaflow-docs
Apr 2020 - Aug 2022
Contributions:3 reviews, 161 commits, 33 PRs in 2 years 4 months
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