Job Description
Join Nexus Labs at the forefront of quantum-AI convergence to build tomorrow's computational reality today. We're pioneering next-generation neural networks operating at quantum coherence scales, requiring candidates who thrive at the intersection of theoretical physics and machine learning innovation.
This role offers unparalleled access to our $50M quantum computing infrastructure and collaborative partnerships with MIT, Caltech, and NASA. You'll shape the algorithms that will redefine computational possibilities by 2026.
Responsibilities
- Design and implement hybrid quantum-classical neural architectures for exponential computational gains
- Develop error-correction protocols for quantum machine learning models
- Lead cross-functional teams of physicists and data scientists on prototype development
- Publish breakthrough research in Nature/Science journals and industry conferences
- Secure $2M+ in DARPA/NASA research grants for quantum-AI initiatives
- Advise C-suite on quantum computing roadmap integration into enterprise systems
Qualifications
- PhD in Quantum Computing, Theoretical Physics, or Machine Learning (or equivalent experience)
- 5+ years implementing quantum algorithms in Qiskit/Cirq frameworks
- Published work in top-tier quantum/AI publications (h-index >15)
- Expertise in tensor networks and quantum circuit optimization
- Proficiency in Python, TensorFlow Quantum, and high-performance computing
- Clearance for government research collaboration (or ability to obtain)
- Track record of translating theoretical concepts into scalable prototypes