Max Fitton
Senior Software Engineer II at Carta
United States
Summary
🤩
Rockstar🎓
Top SchoolMax Fitton is a Senior Software Engineer II with 13 years of experience building distributed systems and developer-facing tools, currently contributing at Carta. He has deep hands-on expertise in Ray's runtime and dashboard—having led the open-source Ray Dashboard at Anyscale and made core runtime improvements touching actor state and task resubmission—which underscores his strengths in debugging and visualization for large-scale ML workloads. His background spans cloud and infrastructure work at Salesforce (OpenStack/private cloud) and product-focused engineering at startups, giving him a rare blend of low-level runtime and user-facing UI experience. Collected across roles, he’s driven API migrations, improved GPU visibility, and refactored critical C++ and backend logic to make complex distributed systems more observable and reliable.
13 years of coding experience
6 years of employment as a software developer
Bachelor of Arts (B.A.) Computer Science, Bachelor of Arts (B.A.) Computer Science at University of California, Berkeley
English, French
Stackoverflow
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Github Skills (5)
ray10
distributed-systems10
c-language10
cprogramming-language10
actor-model10
Programming languages (3)
Github contributions (5)
ray-project/ray
May 2020 - Jan 2021
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 release, 71 reviews, 86 commits in 7 months
Contributions summary:Max primarily focused on refactoring and enhancing the Ray runtime, specifically in the NodeManager component. Their contributions involved renaming variables to improve code clarity and correcting logic for actor reconstruction and task resubmission. The changes indicate a focus on the core distributed runtime of Ray, touching on actor state management and object handling, which are critical for distributed computing. The commit messages also mention changes to the underlying C++ code.
pythonconsistsruntimetensorflowserving
mfitton/ray
Apr 2020 - Jan 2021
A fast and simple framework for building and running distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
Contributions:399 pushes, 121 branches in 8 months
scalableraydistributed-applicationshyperparametersimple-framework
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