Job Description
Join Nexus Labs at the forefront of 2026's technological revolution. We're seeking a visionary Quantum AI Research Lead to architect the next generation of intelligent systems. This role bridges quantum computing and artificial intelligence, driving breakthroughs in machine learning optimization and computational theory. You'll lead a cross-functional team of physicists, engineers, and data scientists to develop scalable quantum neural networks that will redefine industries. Our state-of-the-art facility in San Francisco offers unparalleled resources for experimentation and collaboration, including access to IBM Quantum and D-Wave systems. We provide competitive equity packages, flexible work arrangements, and a commitment to your professional growth through our Innovation Fellowship Program.
Responsibilities
- Design and implement quantum algorithms for machine learning acceleration
- Lead research initiatives in quantum neural networks and hybrid quantum-classical systems
- Collaborate with hardware teams to optimize quantum circuit designs for practical AI applications
- Publish findings in peer-reviewed journals and present at international conferences
- Mentor junior researchers and foster a culture of scientific excellence
- Secure funding through NSF and DARPA grants for cutting-edge projects
- Develop roadmaps for commercializing quantum AI solutions by 2026
Qualifications
- PhD in Quantum Computing, Physics, or Computer Science with 5+ years research experience
- Published work in Nature/Science or top-tier quantum computing conferences
- Proficiency in quantum programming frameworks (Qiskit, Cirq) and AI frameworks (TensorFlow, PyTorch)
- Experience with superconducting qubit systems or trapped-ion quantum processors
- Demonstrated ability to lead multidisciplinary research teams
- Strong background in computational complexity theory and quantum information theory
- Track record of securing government or industry research grants
- Entrepreneurial mindset with interest in commercializing research