Job Description
Join Nexus Future Labs at the forefront of 2026's technological revolution as we pioneer the next generation of Quantum-AI hybrid systems. We seek a visionary Quantum AI Architect to design and implement groundbreaking solutions that bridge quantum computing with artificial intelligence. This role offers unparalleled opportunity to shape the future of computational intelligence while working with Nobel Prize-winning researchers and cutting-edge infrastructure. Our Austin headquarters features state-of-the-art labs and a culture that celebrates bold innovation.
As a key member of our Advanced Systems Division, you'll lead initiatives that will redefine industries from healthcare to finance. We provide competitive benefits including equity packages, flexible work arrangements, and dedicated R&D time for personal breakthrough projects.
Responsibilities
- Design and implement quantum-AI hybrid architectures for next-generation computational systems
- Lead cross-functional teams of quantum physicists and ML engineers in prototype development
- Develop quantum algorithms optimized for AI training and inference processes
- Conduct feasibility studies on quantum advantage applications for enterprise-scale problems
- Collaborate with academic partners to publish breakthrough research in Nature/Science journals
- Establish quantum security protocols for AI model protection and data integrity
- Mentor junior researchers in quantum machine learning methodologies
Qualifications
- PhD in Quantum Computing, Theoretical Physics, or Computational Mathematics (or equivalent experience)
- 5+ years experience in quantum algorithm development and AI system architecture
- Proficiency with quantum programming frameworks (Qiskit, Cirq, PennyLane)
- Published research in quantum machine learning or quantum AI applications
- Expertise in Python/C++ with deep learning frameworks (PyTorch/TensorFlow)
- Demonstrated experience with cloud quantum computing platforms (IBM Quantum, AWS Braket)
- Strong background in complex mathematical modeling and optimization techniques