Job Description
Join Nexus Dynamics at the forefront of 2026's technological revolution. We're seeking a visionary Quantum AI Research Scientist to pioneer the next generation of hybrid quantum-neural systems. This role offers unparalleled opportunity to shape humanity's computational future while working in our state-of-the-art Austin Innovation Hub.
You'll lead groundbreaking research in quantum machine learning, develop novel algorithms for quantum supremacy, and collaborate with Nobel laureates and industry pioneers. Our dynamic environment combines startup agility with enterprise resources, offering competitive equity packages and unlimited R&D budget.
As we prepare for the quantum commercialization wave expected in 2026, your work will directly impact industries from pharmaceuticals to climate modeling. We provide cutting-edge quantum hardware access through our partnerships with IBM, Google Quantum AI, and Rigetti Computing.
Responsibilities
- Design and implement hybrid quantum-classical neural networks for complex optimization problems
- Develop novel quantum algorithms achieving exponential speedups in machine learning tasks
- Lead cross-functional teams in prototyping quantum AI solutions for Fortune 500 clients
- Author peer-reviewed publications and contribute to open-source quantum frameworks
- Bridge theoretical quantum physics with practical AI deployment in production environments
- Advise on quantum-resistant cryptography systems for 2026's security landscape
- Present breakthrough findings at premier conferences like Q2B and NeurIPS
Qualifications
- PhD in Quantum Computing, Theoretical Physics, or Machine Learning (or equivalent expertise)
- Proven experience with quantum programming languages (Qiskit, Cirq, Q#)
- Publication record in quantum machine learning or quantum algorithms
- Mastery of Python/C++ with deep learning frameworks (PyTorch/TensorFlow)
- Expertise in quantum error correction and fault-tolerant architectures
- Familiarity with quantum hardware constraints (IBM Q, Rigetti, IonQ)
- Strong background in linear algebra, probability, and information theory
- Experience leading technical teams and managing research projects