Job Description
Join Nexus Quantum Dynamics at the forefront of the 2026 technological revolution. We're pioneering the fusion of quantum computing and artificial intelligence to solve humanity's most complex challenges. As a Quantum AI Research Engineer, you'll architect next-generation systems that will redefine computing paradigms. Our state-of-the-art San Francisco lab offers unparalleled resources for breakthrough research in quantum machine learning, cryptography, and computational modeling. This is your opportunity to shape the future of technology while working with Nobel laureates and industry pioneers in an environment that celebrates bold innovation.
Why Nexus Quantum Dynamics? We offer competitive equity packages, flexible work arrangements, and continuous learning stipends. Our commitment to pushing boundaries extends beyond technology – we foster a culture of intellectual curiosity and cross-disciplinary collaboration that accelerates breakthrough discoveries.
Responsibilities
- Design and implement quantum algorithms for AI optimization and neural network acceleration
- Develop hybrid quantum-classical computing frameworks for real-time data processing
- Lead research initiatives in quantum-resistant cryptography and secure AI systems
- Create simulation environments for quantum machine learning model validation
- Collaborate with hardware teams to co-design quantum processors optimized for AI workloads
- Author peer-reviewed publications and present findings at international conferences
- Mentor junior researchers and contribute to open-source quantum AI frameworks
Qualifications
- PhD in Quantum Computing, AI, Physics, or Computer Science (or equivalent experience)
- Expertise in quantum programming languages (Qiskit, Cirq, Q#) and circuit optimization
- Proven track record in machine learning frameworks (TensorFlow, PyTorch) with quantum applications
- Strong background in quantum information theory and error correction techniques
- Experience with high-performance computing and parallel processing architectures
- Demonstrated ability to translate complex quantum concepts into practical AI solutions
- Publication record in top-tier quantum/AI conferences (e.g., QIP, NeurIPS, ICML)