Raymond Peck
CTO Principal Engineer AI Advisor Co-Founder at Progressive Ventures
Redwood City, California, United States
Summary
🤩
Rockstar🎓
Top SchoolRaymond Peck is a seasoned engineering leader and CTO with 12+ years of experience building production-grade AI, distributed systems, and scalable platforms from chip-level CPU design to cloud-native ML services. He co-founded and led engineering at multiple startups, shipped core backend features for the widely used open-source H2O machine-learning platform, and repeatedly accelerated delivery by integrating practical ML and DevOps practices. His hands-on work ranges from designing AutoML and REST frameworks at H2O to single-handedly building agentic AI stacks on GCP and improving IoT ML recall/precision for fleet analytics. Based in Redwood City, he blends deep systems engineering (including past CPU/embedded work that powered major consoles) with product-focused ML leadership and investor-facing diligence. Notably, he leverages “vibe coding” tools like Claude Code to dramatically speed prototyping, reflecting a pragmatic embrace of emergent AI tooling alongside rigorous software engineering.
12 years of coding experience
27 years of employment as a software developer
BS, Electrical Engineering, BS, Electrical Engineering at Wayne State UniversityMS, Electrical Engineering (computer architecture specialty) and most of an MSCS, MS, Electrical Engineering (computer architecture specialty) and most of an MSCS at Stanford University
Stackoverflow
11reputation
4kreached
2answers
0questions
Github Skills (14)
javas10
api-rest10
rest-api10
api-design10
restful-api10
java10
serialization9
data-serialization9
data-structures8
version-control8
data-structure8
mypy6
h2o6
python6
Programming languages (7)
Github contributions (5)
h2oai/h2o-3
Jun 2014 - May 2018
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Role in this project:
Backend Developer
Backend DeveloperContributions:720 commits, 93 PRs, 345 pushes in 3 years 11 months
Contributions summary:Raymond primarily worked on the back-end of the H2O platform, modifying and improving existing core Java code. They addressed issues in the REST API by unbreaking and fixing endpoints, including the `/3/Jobs` and `/3/ModelBuilders` endpoints. The user also implemented and refactored various components, such as schema metadata, and ensured the code was compatible with different Java build configurations.
automldeep-learningelastic-netgbmgradient-boosting
GeoFlow-ai/dacite
May 2023 - Apr 2024
Simple creation of data classes from dictionaries. Added ability to change field names, and get values from deep in the input dict.
Contributions:2 pushes, 1 branch in 11 months
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