Job Description
Join Nexus Labs at the forefront of technological evolution as we pioneer the next wave of innovation in 2026. We seek a visionary Quantum AI Research Lead to architect groundbreaking solutions at the intersection of quantum computing and artificial intelligence. Our Austin-based team operates in a state-of-the-art research facility dedicated to pushing the boundaries of computational science. This role offers unparalleled opportunities to shape the future of technology while collaborating with Nobel laureates and industry pioneers.
As a key member of our elite research division, you'll lead cross-functional teams in developing quantum algorithms, optimizing machine learning models, and creating next-generation AI frameworks. We provide competitive equity packages, flexible work arrangements, and access to cutting-edge quantum hardware. If you're driven to solve humanity's most complex challenges through quantum-AI convergence, this is your moment.
Responsibilities
- Architect and implement quantum AI algorithms leveraging Qiskit and Cirq frameworks
- Lead research teams in developing hybrid quantum-classical ML models for 2026-scale applications
- Collaborate with hardware engineers to optimize quantum circuit designs for NISQ-era processors
- Publish breakthrough research in top-tier journals and present at major conferences
- Secure $1M+ in research grants from NSF and DARPA initiatives
- Mentor PhD researchers and build quantum-AI curriculum for internal talent development
- Partner with industry leaders to commercialize quantum-AI solutions in finance and healthcare
Qualifications
- PhD in Quantum Computing, Machine Learning, or Computational Physics
- 5+ years of hands-on experience with quantum programming (Qiskit, Cirq, or Q#)
- Published research in Nature/Science or equivalent top-tier journals
- Expertise in quantum error correction and fault-tolerant architectures
- Proven track record of securing federal research grants
- Deep understanding of transformer architectures and large-scale ML optimization
- Experience leading cross-disciplinary research teams of 10+ scientists
- Strong background in quantum cryptography and information theory