Lakshmi Kumar
Member Of Technical Staff at AMD
San Jose, California, United States
Summary
👤
Senior🎓
Top SchoolLakshmi Kumar is a software engineer with nine years of experience focused on machine learning and computer vision at AMD, where she progressed from SDE2 to Member of Technical Staff. Based in San Jose, she brings a strong systems and embedded background from electrical engineering and hands-on internships, blending low-level hardware understanding with production ML software. Her work spans model-driven computer vision features and scalable engineering practices within a high-performance silicon company. Known for bridging academic rigor from a Computer Engineering master’s at Rutgers with pragmatic product delivery, she thrives on turning research ideas into deployable vision solutions. Unusually for an ML-focused engineer, she also carries early-career experience building web backends and AWS-backed media workflows, giving her a broad, full-stack perspective.
9 years of coding experience
6 years of employment as a software developer
Bachelor’s Degree Electrical Electronics and Communications Engineering, Bachelor’s Degree Electrical Electronics and Communications Engineering at PES UniversityMaster’s Degree Computer Engineering, Master’s Degree Computer Engineering at Rutgers University
English, Hindi, Tamil, Kannada, Malayalam
Github Skills (75)
feature-extraction10
opencl10
windows-machine-learning10
bitwise10
onnx10
neural-network10
object-detection10
computer-vision10
cpu10
virtual-reality10
histogram10
amd10
machine-learning10
inference-engine10
inference10
Programming languages (3)
Github contributions (5)
LakshmiKumar23/rpp
Jul 2020 - Mar 2025
Radeon Performance Primitives (RPP) library is a comprehensive high performance computer vision library for AMD (CPU and GPU) with HIP and OpenCL back-ends.
Contributions:1 review, 1 PR, 42 pushes in 4 years 9 months
amdhipprimitivesopenclcpu
LakshmiKumar23/MIVisionX-Neural-Net-Workflow
Aug 2020 - Aug 2022
MIVisionX Infrastructure for Neural Net Training and Inference with Optimized Data Augmentation through RALI
Contributions:6 reviews, 2 PRs, 56 pushes in 2 years
deep-learninginferenceinfrastructuretrainingoptimized
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