Job Description
Join Nexus Innovations at the forefront of technological evolution as we pioneer the next generation of quantum AI systems. We're seeking a visionary 2026 Quantum AI Research Lead to architect breakthrough solutions that will redefine human-machine interaction. This is your chance to shape the future of computing in our state-of-the-art San Francisco lab, where interdisciplinary teams converge to solve humanity's most complex challenges.
As a key architect of our 2026 roadmap, you'll lead a cohort of world-class researchers in developing hybrid quantum neural networks. You'll collaborate with Nobel laureates and industry disruptors to create algorithms that transcend classical computing limitations. We offer unparalleled resourcesâincluding our proprietary 512-qubit quantum simulatorâand a culture that rewards bold experimentation.
Your impact will extend beyond research: you'll mentor the next generation of quantum pioneers, guide patent strategy, and advise our board on emerging ethical frameworks for advanced AI. This role combines scientific rigor with strategic vision, offering unparalleled influence in the quantum revolution.
Responsibilities
- Architect and lead development of quantum AI systems for 2026 deployment
- Mentor interdisciplinary research teams specializing in quantum machine learning
- Collaborate with hardware teams to optimize quantum-neural interfaces
- Develop ethical frameworks for advanced autonomous AI systems
- Secure $5M+ in research grants and partnerships
- Author breakthrough publications in Nature/Science journals
- Guide patent strategy for quantum AI innovations
Qualifications
- PhD in Quantum Computing, AI, or related field with 10+ years R&D
- Published research in quantum machine learning or quantum neural networks
- Expertise in at least one quantum programming framework (Qiskit, Cirq, etc.)
- Proven track record of securing federal/private research grants
- Experience leading teams of 15+ researchers in high-stakes environments
- Deep understanding of quantum error correction and fault tolerance
- Strong background in AI ethics and responsible innovation frameworks