Mohammed Affan
Software Engineer at Arena
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolMohammed Affan is a software engineer based in New York with a decade of experience building production-grade systems spanning distributed architectures, audio pipelines, and machine learning platforms. A NYU MS graduate with a 3.889 GPA, he has led core orchestration and audio-input redesigns at Amazon that cut user-perceived latency by up to 50% and delivered features used by millions. His work blends backend engineering, test automation, and ML deployment—evident from contributions to Theano/PyTensor where he fixed edge-case bugs, added tensor indexing features, and optimized convolution paths during a Google Summer of Code project. Currently at Arena, he continues to bridge distributed systems and ML, pairing rigorous academic training with hands-on delivery and a knack for improving robustness in critical libraries.
10 years of coding experience
3 years of employment as a software developer
Master of Science - MS, Computer Science, 3.889, Master of Science - MS, Computer Science, 3.889 at New York UniversityScience, Science at Sri Bhagawan Mahaveer Jain CollegeHigh School, High School at Sri aurobindo memorial SchoolBachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Dayananda Sagar College of Engineering, BANGALORE
Hindi, English
Github Skills (11)
tensorrt10
tensor10
tensorflow10
operation10
python10
theano10
test-automation10
testing10
linear-algebra9
debug9
numerical-computing8
Programming languages (7)
Github contributions (5)
Theano/Theano
Jan 2017 - Sep 2017
Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It is being continued as PyTensor: www.github.com/pymc-devs/pytensor
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:183 commits, 18 PRs, 156 comments in 7 months
Contributions summary:Mohammed focused on improving the robustness of the Theano library by addressing bugs related to default values in function modules. They fixed issues in `compile/function_module.py` that arose when default values were set in parameters, and added tests to `compile/tests/test_function_module.py` to verify correct behavior, particularly in error handling. Furthermore, they contributed to the functionality of tensor operations by implementing indexing with empty lists and adding corresponding tests. They also made updates by adding the L_op in the scalar/basic.py.
python-librarymathmulti-dimensionalpythonevaluate
affanv14/Theano
Jan 2017 - Sep 2017
Contributions:204 pushes, 89 branches in 7 months
python-librarymulti-dimensionalpythonevaluatemathematical-expressions
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