Job Description
Join Nexus Quantum Dynamics at the forefront of 2026's technological revolution! We're pioneering quantum machine learning solutions that will redefine industries. As a Quantum Machine Learning Engineer, you'll architect and deploy hybrid quantum-classical AI systems to solve previously unsolvable problems. Our state-of-the-art lab in San Francisco offers unparalleled resources to push the boundaries of computational science. If you're passionate about merging quantum physics with artificial intelligence to create tomorrow's innovations, this is your opportunity to shape the future.
Responsibilities
- Design and implement quantum algorithms for machine learning applications
- Develop hybrid quantum-classical neural network architectures
- Optimize quantum circuits for real-world AI workloads
- Collaborate with physicists to translate quantum phenomena into ML models
- Lead research on quantum advantage in data analysis and pattern recognition
- Document breakthroughs in peer-reviewed publications and technical whitepapers
- Mentor junior engineers in quantum computing best practices
Qualifications
- PhD in Computer Science, Physics, or related field (MS with exceptional experience)
- 3+ years in quantum computing or advanced AI research
- Proficiency in quantum programming languages (Qiskit, Cirq, Q#)
- Strong foundation in machine learning frameworks (PyTorch, TensorFlow)
- Experience with high-performance computing and GPU acceleration
- Published work in quantum computing or top-tier ML conferences
- Demonstrated ability to translate complex theories into practical solutions