Job Description
Join Nexus Quantum Labs at the forefront of technological evolution as we pioneer the convergence of quantum computing and artificial intelligence. We're seeking a visionary Quantum AI Integration Specialist to architect and deploy next-generation solutions that will redefine industries by 2026. In this role, you'll collaborate with Nobel laureate advisors to translate theoretical quantum algorithms into scalable AI frameworks, working in our state-of-the-art facility with access to IBM Quantum and D-Wave systems. Our Austin hub offers unparalleled resources for innovation, including dedicated quantum annealing labs and a $50M R&D budget. We offer competitive equity packages, flexible hybrid work arrangements, and comprehensive benefits including quantum computing certifications and tuition reimbursement for advanced degrees.
Responsibilities
- Design and implement hybrid quantum-classical AI architectures for enterprise clients in finance, healthcare, and logistics sectors
- Develop error-correction protocols to optimize qubit stability in real-time machine learning environments
- Lead cross-functional teams of physicists, data scientists, and hardware engineers to deploy quantum-optimized neural networks
- Create proprietary quantum simulation frameworks using Qiskit and Cirq to accelerate AI model training
- Establish quantum security protocols for federated learning systems using quantum key distribution (QKD)
- Present breakthrough findings at international quantum-AI symposiums and publish in Nature Quantum Information
- Mentor junior researchers in quantum machine learning algorithms and tensor network methodologies
Qualifications
- PhD in Quantum Computing, Physics, or Computer Science with 5+ years of applied quantum-AI integration experience
- Expertise in quantum algorithms (Shor's, Grover's, VQE) and their implementation on quantum hardware
- Proficiency in quantum programming languages (Q#, Qiskit, Cirq) and classical AI frameworks (PyTorch, TensorFlow)
- Published research in quantum machine learning or quantum neural networks (arXiv/IEEE journals)
- Experience with quantum annealing platforms (D-Wave Advantage) and superconducting qubit systems (IBM Quantum)
- Deep understanding of quantum error correction codes (surface, topological) and fault-tolerant computing
- Certification in quantum computing from IBM, Google, or Microsoft Azure Quantum
- Strong background in high-performance computing and distributed quantum systems architecture