Job Description
Join Nexus Quantum Dynamics at the forefront of 2026's technological revolution. We're seeking a visionary Quantum AI Systems Architect to pioneer the fusion of quantum computing and artificial intelligence. This role offers unparalleled opportunity to shape the future of computational science while working with cutting-edge hardware and algorithms in our state-of-the-art San Francisco lab.
As a key innovator, you'll design hybrid quantum-classical systems that solve previously impossible problems across cryptography, materials science, and optimization. Our collaborative environment encourages bold thinking and rapid prototyping, with resources including our 1000-qubit quantum processor and dedicated AI research cluster.
Competitive compensation includes equity, comprehensive benefits, and flexible work arrangements. We invest heavily in professional development through our Quantum Innovation Academy and provide relocation assistance for top global talent.
Responsibilities
- Design and implement hybrid quantum-AI architectures for enterprise-scale applications
- Develop novel quantum machine learning algorithms leveraging 2026-era hardware capabilities
- Lead cross-functional teams of physicists, AI specialists, and software engineers
- Optimize quantum circuits for error correction and computational efficiency
- Translate complex quantum concepts into actionable business solutions
- Drive R&D initiatives in quantum cryptography and secure AI systems
- Collaborate with academic institutions to publish breakthrough research
Qualifications
- PhD in Quantum Computing, Physics, or Computer Science (or equivalent experience)
- Expertise in quantum programming frameworks (Qiskit, Cirq, Q#)
- Proven track record in AI/ML system architecture at scale
- Deep understanding of quantum error correction and fault-tolerant computing
- Strong background in distributed systems and high-performance computing
- Experience with cloud quantum platforms (AWS Braket, Azure Quantum)
- Published research in quantum machine learning or related fields
- Ability to communicate complex technical concepts to diverse stakeholders