Job Description
Join Nexus Future Labs at the frontier of computational evolution! We're pioneering the next generation of quantum-AI hybrid systems that will redefine 2026's technological landscape. As a Quantum AI Research Engineer, you'll architect and deploy breakthrough algorithms at the intersection of quantum computing, machine learning, and neuromorphic engineering. Our state-of-the-art San Francisco facility offers unparalleled resources for transforming theoretical physics into real-world applications.
This role is ideal for visionaries who thrive at the bleeding edge of science and technology. You'll collaborate with Nobel laureates and industry disruptors to develop proprietary quantum neural networks capable of solving previously intractable problems in drug discovery, climate modeling, and materials science.
Responsibilities
- Design and implement quantum machine learning algorithms using Qiskit and TensorFlow Quantum
- Develop neuromorphic computing architectures for real-time quantum-AI hybrid processing
- Lead prototyping of quantum neural networks on superconducting qubit platforms
- Optimize quantum circuit performance for fault-tolerant operations at scale
- Collaborate with cross-functional teams to commercialize quantum-AI solutions
- Publish research in top-tier journals (Nature Quantum, Science AI) and industry whitepapers
Qualifications
- PhD in Quantum Computing, Theoretical Physics, or Computer Science (or equivalent research experience)
- Expertise in quantum programming languages (Q#, Qiskit, Cirq) and quantum error correction
- Proficiency in Python, TensorFlow/PyTorch, and high-performance computing frameworks
- Published research in quantum machine learning or quantum information theory
- Experience with superconducting qubit platforms or trapped-ion systems
- Strong background in computational complexity theory and quantum algorithms