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Mathematic Engine — The core C++/CUDA tensor library ( I am working on this currently )

Neural Network & Data — Building the actual network logic using our API and writing the parser for the MNIST dataset ((Note: You can start writing this now using the header file, even before my backend is fully compiled!))

Core Engine Tester — The QA lead. Setting up GitHub Actions, writing unit tests to compare our math against expected outputs, and keeping the build stable..

CPython API designer — The bridge engineer. Using ctypes or similar to glue our raw C++ engine to a Python runtime.

Frontend Dashboard — Building the interface to display our execution metrics and Cost-Benefit Analysis graphs.

Documentation — One who will document the whole build.

The Frontend and Documentation sectors pair together perfectly, as they both focus on the final presentation and report generation for the professor. I suggest one person takes point on both to streamline the final deliverable.