Job Description
Join NeuroCore Systems at the forefront of 2026's technological revolution as we pioneer the convergence of quantum computing and artificial intelligence. We seek a visionary Quantum AI Research Lead to architect breakthrough solutions that will redefine computational possibilities. This role offers unparalleled opportunities to shape humanity's digital future while working with world-class scientists in our state-of-the-art San Francisco R&D hub.
NeuroCore provides a dynamic environment where your expertise will directly impact next-generation AI systems, quantum algorithms, and hybrid computing architectures. You'll lead cross-disciplinary teams pushing the boundaries of machine learning, cryptography, and computational physics while collaborating with industry pioneers and academic institutions.
Responsibilities
- Architect and execute quantum AI research roadmap targeting 2026 technological inflection points
- Lead development of hybrid quantum-classical machine learning models for enterprise applications
- Drive innovation in quantum neural networks and error mitigation protocols
- Collaborate with hardware teams to optimize quantum-AI co-design strategies
- Publish groundbreaking research in top-tier journals and conferences
- Secure and manage multi-million dollar research grants from government and private sectors
- Mentor next-generation quantum AI researchers and build high-performance teams
Qualifications
- PhD in Quantum Computing, AI, Computational Physics, or equivalent field with 8+ years research experience
- Proven track record of publishing in Nature/Science or top-tier quantum/AI conferences
- Expertise in quantum machine learning algorithms and quantum circuit optimization
- Deep knowledge of quantum error correction, fault tolerance, and hardware-software co-design
- Experience managing research teams and securing competitive funding
- Proficiency in quantum programming languages (Qiskit, Cirq, Q#) and high-performance computing
- Strong background in at least one classical ML framework (PyTorch, TensorFlow)