Ang Qian
DevOps Engineer at IDEMIA
Singapore
Summary
🤩
Rockstar🎓
Top SchoolAng Qian is a DevOps engineer based in Singapore with a decade of experience bridging production support, CI/CD and cloud-native tooling across public-sector and enterprise projects. Comfortable troubleshooting Linux and Kubernetes incidents, he has operationally managed Helm charts, Ansible playbooks, Jenkins pipelines and observability stacks like Grafana and OpenSearch. A final-year NUS Mathematics + Data Science student who contributes to probabilistic ML codebases, he pairs hands-on DevOps delivery with a strong interest in Bayesian deep learning and generative models—bringing research curiosity to practical deployments. Notably, his open-source work on the pyprobml repository demonstrates deep familiarity with probabilistic modeling implementations beyond typical infrastructure responsibilities.
10 years of coding experience
2 years of employment as a software developer
Diploma, Marketing, 3.04/4.0, Diploma, Marketing, 3.04/4.0 at Temasek PolytechnicBachelor's degree, Computing and Information Systems, Graduate with First Class Honors, Bachelor's degree, Computing and Information Systems, Graduate with First Class Honors at University of LondonGCE 'O' Level, GCE 'O' Level, GCE 'O' Level, GCE 'O' Level at Beatty Secondary School
English, Chinese
Github Skills (8)
machine-learning10
probabilistic-programming10
python10
matplotlib9
scipy9
tensorflow7
jax7
pytorch7
Programming languages (8)
Github contributions (5)
probml/pyprobml
Apr 2021 - Sep 2022
Python code for "Probabilistic Machine learning" book by Kevin Murphy
Role in this project:
ML Engineer & Data Scientist
ML Engineer & Data ScientistContributions:3 reviews, 225 commits, 11 PRs in 1 year 5 months
Contributions summary:Ang made significant contributions to implementing and converting machine learning models within the repository. They focused on refactoring existing code to Python and implemented new models for tasks like beta distribution and rejection sampling. Their work also included creating and uploading model implementations for tasks like Potts models and Ising models, showcasing a strong understanding of probabilistic machine learning and model implementation.
pythonpmlflaxcolabpymc3
Neoanarika/Implementing-the-PowerSign-and-AddSign-rule
Dec 2017 - Oct 2018
Implementing the update rule found in Neural Optimizer search with Reinforcement learning
Contributions:71 commits, 1 PR, 83 pushes in 9 months
rulereinforcement-learningupdateoptimizerreinforcement
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