Elena Tapia
Quantum Software Engineer at IBM
Zurich, Zurich, Switzerland
Summary
🤩
Rockstar🎓
Top SchoolElena Tapia is a quantum software engineer based in Zurich with six years of experience building across the quantum stack—from applications in optimization, machine learning and chemistry to algorithms, compilation and hardware interfacing. At IBM Quantum she’s been a key open-source contributor and co-maintainer of the widely used Qiskit SDK, driving features in fidelity primitives, the VQD eigensolver and qiskit-ibm-runtime while earning multiple internal awards for scaling quantum optimization. Equally comfortable in Python and Rust (with background in C++ and C#), she blends applied research with product-minded engineering to turn prototypes into production-ready developer tooling. Her career path spans deep learning, robotics and VR, which gives her a practical edge in user-focused design and cross-disciplinary collaboration. Known for strong communication and teamwork, she also advises the Unitary Foundation on microgrants, helping translate early research into viable community projects.
6 years of coding experience
5 years of employment as a software developer
Master of Science in Engineering, Computer Science, Master of Science in Engineering, Computer Science at Keio UniversitySummer Session, Summer Session at Stanford UniversityExperimental Physics Academy, Experimental Physics Academy at University of PennsylvaniaMaster's Degree, Quantum Computing Technologies, Master's Degree, Quantum Computing Technologies at Universidad Politécnica de Madrid
Spanish, English, French, Japanese, German
Github Skills (8)
circuit10
unit-testing10
quantum-computing10
pytorch10
machine-learning10
q-learning10
qiskit10
python10
Programming languages (6)
Github contributions (5)
qiskit-community/qiskit-machine-learning
Jun 2021 - Nov 2022
Quantum Machine Learning
Role in this project:
ML Engineer
ML EngineerContributions:1 release, 113 reviews, 8 commits in 1 year 4 months
Contributions summary:Elena contributed to the Qiskit Machine Learning repository by fixing a batch gradient warning in the TorchConnector tutorial and several other related files. Their commits involved updating and fixing the TorchConnector tutorial, including the implementation of batch support, and refactoring for improved clarity. They also added unit tests for hybrid QNNs and the TorchConnector, demonstrating their involvement in testing and improving the functionality of the quantum machine learning components.
quantum-computingmachine-learningprototypequantum-programming-languagequantum
Qiskit/qiskit
Oct 2021 - Jan 2023
Qiskit is an open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and primitives.
Role in this project:Back-end Developer / Quantum Computing Engineer
Back-end Developer / Quantum Computing EngineerContributions:2 releases, 1514 reviews, 10 commits in 1 year 3 months
Contributions summary:Elena contributed to the Qiskit project by implementing and refining features related to quantum circuit manipulation, particularly in the areas of state fidelity and quantum algorithm implementations. They added new primitives and interfaces for fidelity calculations, refactoring existing code and fixing bugs. Further, the user contributed to the VQD eigensolver with primitives, improving functionality and addressing documentation and unit test issues.
pythonquantum-circuitsquantum-computingcircuitsquantum-circuit
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