David Silver
Staff Software Engineer at Kodiak Robotics
California, United States
Summary
🤩
Rockstar🎓
Top SchoolDavid Silver is a Senior Staff Software Engineer with 14 years of experience building planning, control, simulation, and mapping software for autonomous vehicles, currently leading a team developing self-driving trucks at Kodiak. He blends hands-on engineering—contributing features and core architecture—with people leadership, having progressed from individual contributor roles at Cruise and Voyage to managing multidisciplinary engineering teams. His background spans startups and enterprise, from founding an acquired recruitment-tech company to shaping Udacity’s self-driving curriculum and contributing TensorFlow/LeNet labs used in popular education repos. David pairs deep robotics and control expertise (C/C++, Matlab) with product and business acumen from an MBA at Stanford GSB, enabling him to move research-grade algorithms into production. A thoughtful communicator, he also writes about autonomy on davidsilver.blog, reflecting a habit of making complex technical topics accessible.
13 years of coding experience
16 years of employment as a software developer
MBA, Business, MBA, Business at Stanford University Graduate School of Business4.0, 4.0 at Thomas Jefferson High School for Scient and TechnologyBSE, Computer Science, 3.8, BSE, Computer Science, 3.8 at Princeton University
Spanish, Portuguese
Github Skills (10)
neural-network10
machine-learning10
jupyter-notebook10
convolutional-neural-networks10
tensorflow10
python10
mnist10
data-science10
deep-learning9
computer-vision8
Programming languages (6)
Github contributions (5)
udacity/CarND-LeNet-Lab
Dec 2016 - Jan 2017
Implement the LeNet deep neural network model with TensorFlow.
Role in this project:
ML Engineer
ML EngineerContributions:31 commits, 2 PRs, 19 pushes in 19 days
Contributions summary:David's primary contribution involves the implementation of a LeNet deep neural network model using TensorFlow within the specified repository. The commits showcase the creation of the LeNet lab solution, including the architecture definition and training pipeline. The user's work focuses on defining the network layers, activation functions, and training the model on the MNIST dataset. Further commits include hyperparameter tuning and improvements to the solution notebook.
lenetdeep-learningdeep-neural-networkneural-networktensorflow
udacity/CarND-TensorFlow-Lab
Nov 2016 - Dec 2016
TensorFlow Lab for Self-Driving Car ND
Role in this project:Data Scientist
Data ScientistContributions:8 commits, 3 PRs, 2 pushes in 16 days
Contributions summary:David primarily contributed to the TensorFlow Lab, focusing on improving the existing code and documentation. Their commits included fixing typos, improving explanations related to Min-Max scaling, and updating the TensorFlow Variable initialization function. Furthermore, the user focused on modifying the notebook, specifically in areas involving the neural network training.
vehicle-detectiondeep-learningself-drivingmachine-learningtensorflow
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