Nikolas Tezak
Member Of Technical Staff at OpenAI
Boulder, Colorado, United States
Summary
🤩
Rockstar🎓
Top SchoolNikolas Tezak is a computational physicist-turned-software engineer with 11 years of experience building production-grade systems for quantum computing and large language models. As a Member of Technical Staff at OpenAI he helped build the early API and inference stack, led the Scaling team's execution for GPT-4 training, and returned to IC/TL work after managing critical training infrastructure. Previously he led quantum hardware modeling, calibration, and compilation efforts at Rigetti, contributing to pyQuil and extending noise modeling and control abstractions used by their QVM. Based in Boulder, he blends deep theoretical physics (Stanford PhD) with practical backend and security engineering, notable for implementing noisy-gate Kraus maps and realistic device simulations that bridge lab variability to deployable software. Colleagues rely on him for rigorous numerical analysis, scalable system design, and translating research prototypes into robust, production software.
11 years of coding experience
2 years of employment as a software developer
Non-degree student, Physics, Non-degree student, Physics at Imperial College LondonDiplom (BS+MS), Physics, Diplom (BS+MS), Physics at Ruprecht-Karls-Universität HeidelbergDoctor of Philosophy - PhD, Applied Physics, Doctor of Philosophy - PhD, Applied Physics at Stanford University
German, English, French
Github Skills (8)
quantum-computing10
quil10
python10
numpy10
apidoc9
api9
testing8
documentation7
Programming languages (6)
Github contributions (5)
rigetti/pyquil
Jan 2017 - Dec 2018
A Python library for quantum programming using Quil.
Role in this project:
Back-end Developer & Security Engineer
Back-end Developer & Security EngineerContributions:51 commits, 82 PRs, 134 pushes in 1 year 11 months
Contributions summary:Nikolas contributed to the core functionality of the pyQuil library, adding features to process quantum programs. Their work included the implementation of the `InstructionGroup.extract_qubits()` and functions for defining and applying noisy gates via Kraus maps, which is crucial for simulating quantum computer imperfections. In addition, the user implemented functions to work with and manipulate job metadata, and added helper functions related to the structure of the quantum programs.
python-librarypythonquantum-computingquantumquantum-programming
ntezak/ntezak.github.io
Dec 2020 - Aug 2023
Contributions:6 pushes in 2 years 8 months
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