Job Description
Join Nexus Innovations at the forefront of technological evolution as we pioneer quantum AI systems that will redefine computing by 2026. We're seeking a visionary Quantum AI Research Scientist to architect next-generation algorithms that bridge quantum mechanics and artificial intelligence. In this role, you'll collaborate with Nobel laureates and industry disruptors to develop fault-tolerant quantum neural networks, solve previously unsolvable optimization problems, and create autonomous quantum computing frameworks.
Our Austin-based innovation hub offers unparalleled resources including a 256-qubit quantum processor, dedicated GPU clusters, and $50M annual R&D budget. You'll lead projects with global impact while enjoying Texas' favorable tax climate and vibrant tech ecosystem.
Responsibilities
- Design and implement quantum machine learning algorithms leveraging superposition and entanglement principles
- Develop hybrid quantum-classical neural networks for exponential speedup in pattern recognition
- Create error-correction protocols for quantum AI systems achieving fault tolerance
- Lead research initiatives in quantum optimization for logistics, drug discovery, and climate modeling
- Collaborate with hardware teams to co-design quantum processors optimized for AI workloads
- Publish breakthrough research in Nature/Science journals and present at IEEE Quantum Week
- Mentor PhD candidates in quantum AI through our sponsored fellowship program
Qualifications
- PhD in Quantum Computing, Theoretical Physics, or Machine Learning with 3+ years industry experience
- Published research on quantum algorithms (Shor's, Grover's, VQE variants)
- Proficiency in Qiskit, Cirq, and TensorFlow Quantum frameworks
- Expertise in tensor networks and quantum circuit optimization techniques
- Strong background in linear algebra, probability theory, and information theory
- Experience with high-performance computing environments (HPC, GPU clusters)
- Demonstrated ability to secure $1M+ in government research grants