Job Description
Join the quantum revolution at Nexus Quantum Labs, where we're pioneering the next frontier of artificial intelligence. We seek a visionary Quantum Machine Learning Engineer to architect groundbreaking algorithms that leverage quantum computing's exponential potential. In this pivotal role, you'll develop hybrid quantum-classical systems that solve previously unsolvable challenges in optimization, cryptography, and AI model training. Collaborate with Nobel-caliber researchers in our state-of-the-art facility, pushing the boundaries of computational intelligence while shaping humanity's technological future.
Our engineers work at the intersection of physics, computer science, and advanced mathematics to create transformative solutions. You'll access our 512-qubit quantum processor and partner with teams across biotech, finance, and autonomous systems. If you're passionate about solving problems that classical computers cannot, and ready to build the infrastructure for the next 50 years of innovation, this is your calling.
Responsibilities
- Design and implement quantum machine learning algorithms leveraging quantum circuits and tensor networks
- Develop hybrid quantum-classical neural architectures for enhanced computational efficiency
- Optimize quantum algorithms for error correction and scalability on fault-tolerant quantum processors
- Create research frameworks for quantum data analysis and quantum-enhanced deep learning
- Collaborate with quantum hardware teams to co-design next-generation quantum accelerators
- Lead cross-functional projects applying quantum ML to drug discovery, financial modeling, and materials science
- Publish breakthrough research in leading quantum computing and machine learning journals
Qualifications
- PhD in Quantum Computing, Machine Learning, Physics, or Computer Science (or equivalent experience)
- Expertise in quantum programming frameworks (Qiskit, Cirq, Q#) and quantum circuit design
- Proficiency in Python, TensorFlow/PyTorch, and high-performance computing architectures
- Deep understanding of quantum algorithms (QAOA, VQE, QML kernels) and error mitigation techniques
- Strong background in linear algebra, probability theory, and quantum information theory
- Experience with quantum hardware integration and quantum cloud platforms (IBM Quantum, Amazon Braket)
- Publication record in quantum machine learning or related fields preferred