Christopher Bilger
Staff Software Engineer at Talkiatry
Greater Philadelphia United States
Summary
🤩
Rockstar🎓
Top SchoolChristopher Bilger is a Staff Software Engineer with nine years of experience building full-stack enterprise applications and leading engineering efforts at Talkiatry. He blends hands-on development, testing, and deployment expertise with a background in education and mentorship, shaping teams as well as code. Prior roles at Lockheed Martin sharpened his discipline for robust systems and documentation-driven development. An active FOSS advocate, he contributes to projects like mlrose, improving algorithm implementations and code quality to align with best practices. He holds a Master of Computer Science from Arizona State and a BS in Computer Science from Temple University, pairing formal training with practical delivery. Based in Greater Philadelphia, he’s a student-at-heart who brings curiosity and an educator’s touch to complex engineering problems.
9 years of coding experience
6 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Temple UniversityMaster of Computer Science - MCS, Master of Computer Science - MCS at Arizona State UniversityAssociate of Science - AS, Mathematics, Associate of Science - AS, Mathematics at Bucks County Community College
Stackoverflow
1reputation
49reached
0answers
1question
Github Skills (9)
pep10
python10
code-formatting10
algorithms9
machine-learning8
testing7
php6
sql6
mysql6
Programming languages (8)
Github contributions (5)
gkhayes/mlrose
Oct 2018 - Dec 2018
Python package for implementing a number of Machine Learning, Randomized Optimization and SEarch algorithms.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 review, 57 commits, 13 PRs in 1 month
Contributions summary:Christopher primarily contributed to the codebase by refactoring and formatting existing files to adhere to PEP8 guidelines. They fixed issues related to code style, whitespace, and inconsistent formatting. The commits demonstrate improvements in code quality and standardization across multiple files, including core modules and test files. Additionally, the user made changes to the algorithms and fitness functions to ensure better code quality.
pythonrandomizedoptimizationmachine-learningpython-package
ChristopherBilg/cis4296-starter
Sep 2019 - May 2022
Contributions:2 PRs, 2 pushes, 1 branch in 2 years 8 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.