Khalid Riyaz
Software Engineer at Airbnb
Telangana, India
Summary
🤩
Rockstar🎓
Top SchoolKhalid Riyaz is a software engineer with 8 years of experience building production-grade, scalable systems across cloud, healthcare AI, and ML evaluation platforms. Currently at Airbnb, he has a strong background in backend engineering, microservices, ETL and high-performance NLP pipelines from his work at ConcertAI. He contributed significantly to the open-source EvalAI project (Cloud-CV), streamlining challenge creation, autoscaling evaluation workers on AWS, and adding features like S3 presigned URL support and robust test suites. Khalid combines hands-on coding (Python, Django, AWS, Docker) with production-focused practices—refactoring, testing, and observability—to reliably ship complex features. He also has mentoring experience from Google Code-in and a track record of reducing operational setup time from days to minutes, showing a knack for automating developer and host workflows. Based in Telangana, India, he brings a pragmatic, systems-first approach to turning research and NLP models into deployable services.
8 years of coding experience
3 years of employment as a software developer
BITS Pilani, Birla Institute of Technology and Science12th Grade, 12th Grade at Sri Chaitanya College of EducationICSE, 10th Grade, ICSE, 10th Grade at Nasr School
Github Skills (21)
api-rest10
python10
restful-api10
django10
rest-api10
testing9
unit-testing9
aws9
integration-testing9
test-unit9
unit-test9
test-integration9
docker8
repr8
dockers8
Programming languages (5)
Github contributions (5)
Cloud-CV/EvalAI
Apr 2019 - Sep 2020
:cloud: :rocket: :bar_chart: :chart_with_upwards_trend: Evaluating state of the art in AI
Role in this project:
Backend Developer
Backend DeveloperContributions:33 reviews, 31 commits, 52 PRs in 1 year 5 months
Contributions summary:Khalid primarily contributed to the backend functionality of the EvalAI repository, focusing on resolving bugs and implementing new features related to challenge management and submission processing. They made changes to views, workers, and test files, indicating a strong involvement in the application's core logic. Their work involved refactoring code, addressing merge conflicts, and adding unit/integration tests to improve the system's reliability. Furthermore, the user added features to support challenge templates and S3 presigned URLs.
pythondjangostate-of-the-artangular7tensorflow
KhalidRmb/EvalAI
Jan 2019 - Sep 2020
:cloud: :rocket: :bar_chart: :chart_with_upwards_trend: Evaluating state of the art in AI
Contributions:1 PR, 453 pushes, 59 branches in 1 year 7 months
pythonartchartdata-sciencedeep-learning
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