Job Description
Shape the future at Nexus Quantum Labs, where quantum computing meets artificial intelligence. We're pioneering next-gen systems that will redefine computational boundaries by 2026. Join our elite team to architect hybrid quantum-classical frameworks that solve humanity's most complex challenges. Our state-of-the-art facility in San Francisco offers unparalleled resources and collaborative environments for groundbreaking research.
This role sits at the intersection of quantum physics, machine learning, and distributed systems. You'll work directly with Nobel laureates and industry pioneers to develop scalable quantum neural networks, pushing the limits of what's possible in computational intelligence.
Responsibilities
- Design and implement quantum-classical hybrid architectures for AI acceleration
- Develop error-corrected quantum algorithms for machine learning optimization
- Lead cross-functional teams in prototyping quantum neural network frameworks
- Collaborate on patent-pending quantum computing security protocols
- Research and integrate emerging quantum technologies (photonic, topological qubits)
- Create performance benchmarks for quantum AI systems across industry verticals
- Mentor junior researchers in quantum programming and algorithm design
Qualifications
- PhD in Quantum Computing, Physics, or Computer Science (or equivalent experience)
- 3+ years implementing quantum algorithms on real quantum hardware
- Expertise in Qiskit, Cirq, or similar quantum development frameworks
- Publication record in top-tier quantum computing conferences (QIP, QCE)
- Proficiency in Python, TensorFlow/PyTorch, and low-level quantum circuit design
- Experience with quantum error correction and fault-tolerant systems
- Strong background in distributed computing architectures (Kubernetes, Spark)