Job Description
Join Nexus Quantum Labs at the forefront of 2026's technological revolution. We're seeking a visionary Quantum AI Research Scientist to pioneer breakthroughs that will redefine human capability. In this role, you'll architect next-generation quantum neural networks and hybrid AI systems that solve previously unsolvable challenges in healthcare, climate modeling, and computational physics.
Our state-of-the-art San Francisco campus offers unparalleled resources including 128-qubit quantum processors, exascale computing clusters, and a dedicated team of Nobel Prize-winning mentors. You'll collaborate with interdisciplinary pioneers to develop proprietary quantum algorithms that will power the next generation of autonomous systems and predictive analytics.
This position includes competitive equity, unlimited PTO, and comprehensive wellness benefits. Your work will directly impact humanity's most pressing challenges while shaping the technological landscape for decades to come.
Responsibilities
- Design and implement novel quantum machine learning algorithms for complex pattern recognition
- Lead cross-functional R&D teams in developing hybrid quantum-classical AI architectures
- Develop proprietary quantum neural networks with exponential speed advantages over classical systems
- Translate theoretical quantum computing principles into practical industrial applications
- Author breakthrough research publications in top-tier journals and conferences
- Mentor junior researchers in quantum information theory and quantum algorithm design
- Collaborate with hardware teams to optimize quantum circuit performance for AI workloads
Qualifications
- PhD in Quantum Computing, Theoretical Physics, or Computational Mathematics
- 3+ years of hands-on experience with quantum programming languages (Qiskit, Cirq, Q#)
- Published research in quantum machine learning or quantum information theory
- Expertise in quantum error correction and fault-tolerant computing architectures
- Strong background in linear algebra, quantum mechanics, and computational complexity
- Proven ability to translate theoretical concepts into scalable implementations
- Experience with high-performance computing environments and parallel processing