Job Description
Shape the future by pioneering quantum-AI hybrid systems at Nexus Quantum Labs. We're seeking visionary Research Engineers to develop next-gen computational models that transcend classical limitations. Join our elite team in San Francisco's innovation hub, where you'll collaborate with Nobel laureates and industry disruptors to build solutions for climate modeling, drug discovery, and cryptography.
Our state-of-the-art facility offers unparalleled resources, including quantum annealers, superconducting processors, and GPU-accelerated AI clusters. We provide competitive equity packages, flexible hybrid work options, and dedicated R&D budgets for experimental projects. This is your chance to work at the intersection of quantum physics and artificial intelligence while contributing to humanity's most pressing challenges.
Responsibilities
- Design and implement quantum machine learning algorithms for complex optimization problems
- Develop hybrid quantum-classical computing frameworks using Qiskit, Cirq, and TensorFlow Quantum
- Lead research initiatives in quantum neural networks and quantum-enhanced reinforcement learning
- Collaborate with hardware teams to co-design quantum processors for AI workloads
- Author breakthrough research papers for Nature Physics and IEEE Quantum Journal
- Mentor cross-functional teams in quantum computing principles and implementation
- Secure patents for novel quantum-AI methodologies and system architectures
Qualifications
- PhD in Quantum Computing, Theoretical Physics, or Computer Science (MS with exceptional experience considered)
- Proficiency in quantum programming languages (Q#, Qiskit, Cirq) and quantum circuit design
- Publication record in top-tier quantum/AI conferences (QIP, NeurIPS, ICML)
- Expertise in linear algebra, quantum information theory, and machine learning frameworks
- Experience with quantum hardware interfaces (IBM Q, Rigetti, D-Wave)
- Strong Python/C++ skills with high-performance computing optimization experience
- Demonstrated ability to translate theoretical concepts into practical implementations