Job Description
Join Nexus Labs at the forefront of 2026's technological revolution. We're pioneering the intersection of quantum computing and artificial intelligence to solve humanity's greatest challenges. As a Quantum AI Research Scientist, you'll architect the next generation of intelligent systems that will redefine industries and shape our collective future. Our state-of-the-art facility in San Francisco offers unparalleled resources and a culture where curiosity drives innovation.
We're seeking visionary thinkers who thrive at the edge of possibility. This role offers competitive compensation, equity, and the opportunity to leave an indelible mark on the technological landscape. If you're ready to transform theoretical breakthroughs into practical solutions that will power the 2026 ecosystem, we want to hear from you.
Responsibilities
- Lead cutting-edge research in quantum machine learning algorithms for 2026-era applications
- Develop novel quantum neural network architectures leveraging superposition and entanglement
- Collaborate with cross-disciplinary teams to implement quantum-AI hybrid systems
- Publish breakthrough research in top-tier journals and industry conferences
- Translate theoretical models into scalable prototypes using quantum simulators and hardware
- Secure and manage research partnerships with leading quantum computing providers
- Mentor junior researchers and foster a culture of experimental excellence
Qualifications
- PhD in Quantum Computing, Physics, Computer Science, or related field (or equivalent experience)
- 3+ years of hands-on experience with quantum programming frameworks (Qiskit, Cirq, or similar)
- Proven track record of publishing high-impact research in quantum AI or adjacent fields
- Expertise in machine learning architectures and classical-quantum integration techniques
- Strong mathematical foundation in linear algebra, probability, and information theory
- Experience with cloud-based quantum computing platforms (AWS Braket, IBM Quantum)
- Demonstrated ability to lead complex research projects with ambiguous outcomes