Job Description
Join the vanguard of 2026's technological revolution at Nexus Quantum Labs. We're pioneering the intersection of quantum computing and artificial intelligence to solve humanity's most complex challenges. As a Quantum AI Research Scientist, you'll develop next-generation algorithms that push the boundaries of computational possibility in our state-of-the-art San Francisco facility.
This role offers unparalleled opportunity to shape the future of technology through cutting-edge research, collaboration with Nobel laureates, and access to our quantum annealing infrastructure. You'll contribute to breakthroughs in drug discovery, climate modeling, and cryptography while working with a diverse team of world-class physicists and machine learning experts.
What we offer: competitive equity packages, unlimited PTO, $10k annual learning stipend, and flexible hybrid work arrangements. Your work will directly impact how humanity solves problems in the 2020s and beyond.
Responsibilities
- Design and implement quantum machine learning algorithms for NISQ-era hardware
- Develop novel error-correction protocols for quantum neural networks
- Lead cross-functional research initiatives with AI and quantum physics teams
- Author peer-reviewed publications and patentable quantum AI methodologies
- Optimize quantum-classical hybrid computing workflows for enterprise applications
- Mentor junior researchers and present findings at international conferences
- Collaborate with product teams to translate research into commercial solutions
Qualifications
- PhD in Quantum Physics, Computer Science, or related field (MS with exceptional experience considered)
- 3+ years of hands-on quantum algorithm development experience
- Proficiency in quantum programming languages (Qiskit, Cirq, or Q#)
- Deep understanding of tensor networks and quantum machine learning frameworks
- Published research in quantum computing or AI (arXiv/IEEE journals)
- Expertise in Python, C++, and high-performance computing environments
- Strong background in linear algebra, probability theory, and information theory
- Demonstrated ability to work in fast-paced research environments