Chelsea Lowman
Staff Machine Learning Engineer at Lambda, Inc.
Greater Richmond Region United States
Summary
🤩
Rockstar🎓
Top SchoolChelsea Lowman is a Staff Machine Learning Engineer with 11 years of experience building production ML systems and safe, high-performance software. Based in the Greater Richmond region, she has progressed from software engineer roles at Johns Hopkins APL to senior ML engineering at Neural Magic and Lambda, now leading ML efforts at Lambda. Her work blends systems-level engineering—evident from contributing a safe Rust wrapper for the CUDA toolkit—with applied ML, delivering robust inference and deployment solutions. Chelsea holds an MS in Computer Science from Johns Hopkins and a BS in Mathematics and Computer Science, pairing rigorous academics with practical delivery. She is an active open-source contributor who focuses on reliability, memory-safe GPU integration, and thoughtful design decisions. Colleagues describe her as curious and intentional, consistently translating complex research and tooling into dependable production software.
11 years of coding experience
10 years of employment as a software developer
Johns Hopkins UniversityBachelor of Science (BS) Mathematics and Computer Science, Bachelor of Science (BS) Mathematics and Computer Science at University of Maryland
Github Skills (6)
binding10
cuda10
memory-management10
gpu-programming10
rust10
bind10
Programming languages (7)
Github contributions (5)
coreylowman/cudarc
Sep 2022 - Jan 2023
Safe rust wrapper around CUDA toolkit
Role in this project:
Back-end Developer
Back-end DeveloperContributions:43 releases, 106 reviews, 90 commits in 4 months
Contributions summary:Chelsea primarily focused on developing a safe Rust wrapper around the CUDA toolkit. Their contributions involved initial setup, code generation, and implementing functionalities related to CUDA, including memory management and kernel launching. They implemented and refactored code for CUDA device and module management, along with memory operations, to ensure a safe and reliable interface for CUDA programming in Rust. The user also addressed some compilation issues related to NVRTC.
cudagpu-accelerationcuda-programminggpurust
coreylowman/teeracer
Dec 2021 - Feb 2022
Contributions:60 commits, 4 pushes, 1 branch in 2 months
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