Alana Renda
Founder And Chairman at Readyset
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolAlana Renda is a founder and technology leader with a decade of experience building distributed systems, databases, and ML infrastructure, currently serving as Founder and Chairman of Readyset after four years as its CEO. With a PhD-level background from MIT and a BS from Cornell, she blends deep research credentials with hands-on engineering and startup execution. She has contributed to high-profile open-source AI infrastructure—enhancing Ray’s runtime observability, profiling, and UI heat maps—demonstrating pragmatic improvements to cluster-scale ML tooling. Her career includes research roles at Microsoft, Cornell, and UC Berkeley’s RISELab, reflecting a sustained focus on bridging academic systems research and production services. Known for shipping observable, debuggable distributed systems, she pairs product leadership with low-level backend and DevOps expertise. Based in New York, she quietly favors instrumenting systems for real-world operability as much as algorithmic novelty.
10 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Massachusetts Institute of TechnologyBachelor of Science (B.S.) Computer Science, Bachelor of Science (B.S.) Computer Science at Cornell University
English, French, Russian
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (20)
python10
redis10
distributed-systems10
logging10
ray10
data-science9
deploying9
apidoc9
api9
docker8
performance-tuning8
performance-analysis8
deep-learning8
webui8
performance-measurement8
Programming languages (6)
Github contributions (5)
ray-project/ray
Jun 2017 - Aug 2017
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 & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:19 commits, 63 PRs, 15 comments in 2 months
Contributions summary:Alana primarily focused on enhancing the Ray AI compute engine's functionality. Their contributions included exposing log files through a global state API, enabling the redirection of worker standard output/error to log files, and including worker IDs in task event logs. They also worked on adding task profiling information and incorporating object size and hash in the object table. Additionally, they made changes to enable dumping profiling information and implemented a cluster heat map for the web UI.
pythonconsistsruntimetensorflowserving
alanamarzoev/srmap
Sep 2018 - Apr 2019
Shared reader map
Contributions:57 commits, 70 pushes, 1 branch in 6 months
reactmaptypescriptreader
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