Job Description
Join Nexus Quantum Labs at the forefront of technological evolution as we pioneer quantum-AI fusion systems. We're seeking visionary Quantum AI Systems Architects to design next-gen computational frameworks that will redefine industries by 2026. Our multidisciplinary team operates at the intersection of quantum mechanics, machine learning, and distributed systems to solve humanity's most complex challenges.
As an Architect, you'll architect fault-tolerant quantum neural networks, develop hybrid quantum-classical algorithms, and lead prototype deployments in secure cloud environments. You'll collaborate with Nobel laureates and industry disruptors in our state-of-the-art facility overlooking the Bay Bridge, where we're building the computational infrastructure for 2026 and beyond.
Responsibilities
- Design scalable quantum-AI architectures integrating QPU accelerators with classical ML frameworks
- Develop fault-tolerant quantum error correction protocols for real-time inference systems
- Lead implementation of hybrid quantum-classical optimization algorithms for enterprise clients
- Architect secure quantum communication protocols for distributed AI model training
- Create performance benchmarks for quantum neural networks across diverse industry use cases
- Mentor cross-functional teams in quantum computing principles and practical implementation
- Drive R&D initiatives in quantum machine learning algorithms and quantum-inspired neural networks
Qualifications
- PhD in Quantum Computing, Physics, Computer Science, or equivalent experience
- 5+ years developing quantum algorithms or quantum-inspired machine learning systems
- Expertise in Qiskit, Cirq, or quantum circuit optimization frameworks
- Proficiency in distributed computing architectures (Kubernetes, Spark) and cloud platforms (AWS/Azure/GCP)
- Published research in quantum machine learning or quantum error correction
- Experience leading technical teams in high-stakes R&D environments
- Deep understanding of quantum hardware constraints and error mitigation techniques
- Strong background in Python, C++, and high-performance computing paradigms