Job Description
Join Nexus Labs at the forefront of 2026's technological revolution as we pioneer the next generation of quantum-AI hybrid systems. We seek a visionary Quantum AI Architect to design and implement breakthrough solutions that will redefine computational boundaries. This role offers unparalleled opportunities to shape the future of artificial intelligence, working with cutting-edge quantum hardware and advanced machine learning algorithms in our state-of-the-art Austin facility.
As a key member of our Innovation Division, you'll collaborate with Nobel laureates and industry pioneers to develop scalable quantum neural networks. We provide comprehensive benefits including equity grants, flexible work arrangements, and continuous learning stipends. Your work will directly impact sectors from healthcare to climate modeling, solving humanity's most complex challenges.
Responsibilities
- Design and implement quantum-AI hybrid algorithms for complex optimization problems
- Lead development of fault-tolerant quantum neural networks with 1000+ qubit capabilities
- Collaborate with hardware teams to co-design quantum processors optimized for AI workloads
- Develop novel error correction protocols for quantum machine learning applications
- Create blueprints for quantum-AI integration frameworks compatible with classical HPC systems
- Mentor junior researchers and publish breakthrough findings in top-tier journals
- Secure $5M+ in research grants for quantum-AI initiatives
Qualifications
- PhD in Quantum Computing, Computer Science, or related field (or equivalent experience)
- 5+ years experience in quantum algorithm development and quantum error correction
- Expertise in Python, C++, and quantum programming languages (Qiskit, Cirq)
- Published research in Nature/Science or IEEE Quantum journals
- Proven track record of leading quantum-AI hybrid system implementations
- Deep understanding of tensor networks and quantum machine learning principles
- Experience securing federal research grants (NSF, DOE, DARPA)
- Strong background in high-performance computing architectures