Job Description
Join Nexus Quantum Systems at the forefront of technological evolution. We're pioneering quantum machine learning solutions that will redefine industries by 2026. As a Quantum Machine Learning Engineer, you'll architect hybrid quantum-classical systems to solve previously intractable problems in drug discovery, climate modeling, and financial optimization. Our Austin-based R&D hub offers a dynamic, interdisciplinary environment where your expertise will directly shape tomorrow's computational paradigm.
Why Nexus Quantum? We provide competitive equity packages, flexible hybrid work arrangements, and access to our 128-qubit quantum testbed. Collaborate with Nobel laureates and AI pioneers while advancing humanity's quantum capabilities.
Responsibilities
- Design and implement hybrid quantum-classical ML pipelines for enterprise clients
- Optimize quantum algorithms for NISQ-era hardware constraints
- Develop quantum neural network architectures for pattern recognition tasks
- Lead cross-functional teams in deploying quantum ML prototypes
- Contribute to open-source quantum ML frameworks (Qiskit, PennyLane)
- Translate complex quantum concepts into actionable business solutions
- Drive innovation in quantum data encoding and feature extraction
Qualifications
- PhD in Quantum Computing, Machine Learning, or related field (or equivalent experience)
- Proficiency in quantum programming languages (Qiskit, Cirq, Q#)
- Strong foundation in tensor networks and quantum circuit optimization
- Experience with cloud-based quantum computing platforms (IBM Quantum, Amazon Braket)
- Published research in quantum machine learning or quantum algorithms
- Expertise in Python, TensorFlow/PyTorch, and high-performance computing
- Understanding of quantum error correction and fault-tolerance principles