Sahil Gupta
Software Engineer at Citadel
United States
Summary
🤩
Rockstar🎓
Top SchoolSahil Gupta is a seasoned software engineer with 10 years of experience building reliable, high-performance systems and recent roles scaling infrastructure and teams at bodo.ai before joining Citadel. He holds BS and MS degrees in Computer Science from UIUC and brings a strong foundation in parallel and scientific computing, evidenced by research that accelerated a polymer simulation over 10x and a publication in ASME Journal of Applied Mechanics. Sahil contributes to prominent open-source projects like Numba and IPython, where he improved testing infrastructure, CI, and real-time streaming capabilities—work that touches core tooling used by the Python scientific community. His background spans backend systems, test automation, and developer productivity analytics, with internship experience automating engineering metrics at Bridgewater. Known for pragmatic problem-solving, he blends research-grade rigor with production discipline to deliver robust, well-tested software. A lesser-known strength is his repeated focus on developer experience—improving testing, CI and tooling to make complex systems easier to maintain and extend.
10 years of coding experience
6 years of employment as a software developer
HSC Science, HSC Science at Earthinators Climate SchoolMaster of Science - MS Computer Science, Master of Science - MS Computer Science at University of Illinois Urbana-Champaign
English, Hindi
Github Skills (17)
pytest10
python10
jupyter10
testing10
ipython10
numpy10
parallel-computing10
test-automation10
server-client9
async9
asynchronous9
cicd9
client-server9
compiler-compiler9
cuda9
Programming languages (6)
Github contributions (5)
ipython/ipyparallel
Apr 2021 - Nov 2021
IPython Parallel: Interactive Parallel Computing in Python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:37 reviews, 32 commits, 5 PRs in 7 months
Contributions summary:Sahil primarily focused on enhancing the functionality of the IPython Parallel library. Their contributions include adding UTF-8 decoding for engine identification and implementing streaming output capabilities. They also introduced engine ID integration using partial functions and implemented suggestions to improve code quality and features related to real-time output, thereby improving the user experience within the IPython Parallel environment. Additionally, the user fixed existing tests.
pythonparallelmulticorejupytercomputing
numba/numba
Aug 2021 - Nov 2021
NumPy aware dynamic Python compiler using LLVM
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:3 reviews, 10 commits, 5 comments in 3 months
Contributions summary:Sahil primarily contributed to improving the testing infrastructure and test coverage of the Numba project. This involved adding new tests for caching mechanisms within IPython environments using ipykernel, and expanding the testing suite with matrix multiplication examples. They also made changes to ensure the tests correctly handle caching and IPython-specific configurations. Furthermore, the user added CI setup improvements related to the installation of testing dependencies.
cudapythonparallelnumpynumba
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