Job Description
Join Nexus Quantum Solutions at the forefront of technological evolution in 2026. We're pioneering quantum-entangled AI systems that redefine computational boundaries. As a Quantum Machine Learning Engineer, you'll architect hybrid quantum-classical models to solve previously unsolvable challenges in drug discovery, climate modeling, and autonomous systems. Our Austin-based R&D hub offers cutting-edge lab facilities, collaborative innovation spaces, and competitive benefits including equity in a pre-IPO quantum startup.
Responsibilities
- Design and implement quantum neural networks leveraging Qiskit and Cirq frameworks
- Develop hybrid quantum-classical ML pipelines for high-stakes industry applications
- Optimize quantum algorithms for error correction and coherence time extension
- Collaborate with physicists to translate theoretical quantum advantage into practical ML solutions
- Lead quantum data preprocessing and feature extraction protocols
- Document quantum ML architectures in peer-reviewed publications and patents
Qualifications
- PhD in Quantum Computing, Machine Learning, or Physics (MS with 5+ years experience)
- Proficiency in quantum programming languages (Q#, Qiskit, Cirq)
- Expertise in Python, TensorFlow/PyTorch, and quantum circuit optimization
- Published research in quantum machine learning or related fields
- Experience with quantum hardware platforms (IBM Quantum, Rigetti, IonQ)
- Strong background in linear algebra, quantum mechanics, and information theory