Job Description
Join Nexus Quantum Solutions at the forefront of technological evolution as we pioneer the intersection of quantum computing and artificial intelligence. We're seeking a visionary Quantum AI Research Engineer to develop groundbreaking algorithms that will redefine computational boundaries in 2026 and beyond. You'll collaborate with Nobel laureates and industry disruptors in our Austin-based quantum lab, leveraging state-of-the-art hardware to solve previously unsolvable problems in cryptography, optimization, and machine learning.
This role offers unparalleled opportunities to shape the next generation of computational paradigms while working with a team of world-class physicists, mathematicians, and AI specialists. Our culture celebrates intellectual curiosity and rewards innovation with competitive equity packages and flexible research methodologies.
Responsibilities
- Design and implement novel quantum machine learning algorithms for 2026-era computational challenges
- Develop hybrid quantum-classical frameworks for real-world industrial applications
- Lead experimental validation of quantum AI models using 50+ qubit processors
- Collaborate with hardware teams to optimize quantum circuit architectures for AI workloads
- Publish breakthrough research in top-tier quantum computing and AI journals
- Mentor junior researchers and drive cross-functional innovation initiatives
- Secure federal and private research grants for quantum AI projects
Qualifications
- PhD in Quantum Computing, Physics, Computer Science, or related field (or equivalent industry experience)
- Expertise in quantum algorithms, quantum machine learning, or quantum error correction
- Proficiency in quantum programming frameworks (Qiskit, Cirq, Q#) and classical ML libraries
- Strong background in linear algebra, probability theory, and computational complexity
- Experience with quantum hardware interfaces and cloud quantum computing platforms
- Published research in peer-reviewed quantum/AI conferences (e.g., QIP, NeurIPS)
- Ability to translate theoretical concepts into practical implementations