Job Description
Join Nexus Quantum Labs at the forefront of technological evolution as we pioneer the next wave of quantum-powered AI systems. As a Quantum Machine Learning Engineer, you'll architect hybrid quantum-classical models that redefine computational boundaries in fields from drug discovery to climate modeling. Our multidisciplinary team operates at the intersection of quantum physics, advanced algorithms, and ethical AI development.
This role offers unparalleled opportunities to shape 2026's technological landscape while collaborating with Nobel laureates and industry disruptors. You'll work in our state-of-the-art San Francisco lab, equipped with cutting-edge quantum hardware and a culture that celebrates intellectual curiosity and bold innovation.
Responsibilities
- Design and implement quantum neural networks for complex optimization problems
- Develop hybrid quantum-classical algorithms for real-world industrial applications
- Lead research on quantum advantage in machine learning model training
- Create error mitigation protocols for noisy intermediate-scale quantum systems
- Collaborate with AI ethics teams to ensure responsible quantum AI deployment
- Author peer-reviewed publications on quantum machine learning breakthroughs
- Mentor junior researchers in quantum computing fundamentals
Qualifications
- PhD in Quantum Computing, Machine Learning, or Physics (or equivalent experience)
- Proficiency in quantum programming frameworks (Qiskit, Cirq, or PennyLane)
- Strong background in advanced ML algorithms (transformers, GNNs, reinforcement learning)
- Experience with quantum error correction and fault-tolerant architectures
- Publication record in top-tier quantum/AI conferences (Nature, NeurIPS, etc.)
- Expertise in high-performance computing and parallel processing
- Understanding of quantum hardware constraints (superconducting, ion trap, photonic)
- Commitment to ethical AI development principles