Job Description
Join the frontier of technological evolution as a Quantum AI Research Scientist at FutureTech Innovations. We're pioneering the next wave of computational intelligence where quantum mechanics meets artificial intelligence. As a key member of our R&D team, you'll develop revolutionary algorithms that redefine machine learning paradigms and solve previously unsolvable computational challenges. Our state-of-the-art lab in San Francisco provides unparalleled resources for breakthrough research, with competitive compensation and equity opportunities for those shaping 2026's technological landscape.
We seek visionaries who thrive at the intersection of quantum physics, neural networks, and high-performance computing. You'll collaborate with Nobel laureates and industry disruptors to prototype quantum neural networks, optimize quantum machine learning models, and publish groundbreaking research in Nature and Science. Our culture celebrates intellectual curiosity and offers flexible research parameters with dedicated quantum computing infrastructure including 128-qubit processors and hybrid classical-quantum supercomputers.
Responsibilities
- Design and implement quantum algorithms for machine learning optimization and AI acceleration
- Lead research on quantum neural networks and hybrid quantum-classical AI architectures
- Develop novel error-correction techniques for quantum computing in AI applications
- Collaborate with hardware teams to co-design quantum processors optimized for AI workloads
- Publish peer-reviewed research in top-tier quantum computing and AI conferences
- Mentor junior researchers and contribute to open-source quantum AI frameworks
- Secure patents for breakthrough quantum AI methodologies and applications
Qualifications
- PhD in Quantum Computing, Physics, Computer Science, or related field with 3+ years research experience
- Expertise in quantum programming languages (Qiskit, Cirq, Q#) and quantum circuit design
- Deep knowledge of machine learning frameworks (TensorFlow, PyTorch) and neural network architectures
- Published research in quantum computing or AI at premier conferences (NeurIPS, QIP, Nature)
- Proficiency in high-performance computing environments and parallel processing
- Strong background in linear algebra, probability theory, and quantum information theory
- Experience with quantum hardware platforms (IBM Quantum, Rigetti, IonQ)