Job Description
Join Nexus Quantum Labs at the forefront of technological revolution as we pioneer quantum-enhanced machine learning systems. We're seeking visionary Quantum Machine Learning Engineers to develop groundbreaking algorithms that leverage quantum computing to solve previously unsolvable problems in cryptography, optimization, and AI. Work in our state-of-the-art Austin lab collaborating with Nobel laureates and industry pioneers to shape the computational landscape of 2026 and beyond.
What You'll Achieve:
Design and implement quantum neural networks that outperform classical systems by orders of magnitude. Bridge the gap between quantum hardware and practical ML applications while pioneering new paradigms in quantum data processing. Your innovations will directly impact fields from drug discovery to climate modeling.
Responsibilities
- Develop quantum-enhanced machine learning algorithms for real-world applications
- Optimize quantum circuits for hybrid quantum-classical ML workflows
- Implement error mitigation strategies for noisy quantum systems
- Collaborate with quantum hardware engineers to co-design qubit architectures
- Create novel quantum data encoding techniques for neural networks
- Lead research on quantum advantage in deep learning and reinforcement learning
- Develop quantum-inspired classical algorithms for near-term deployment
Qualifications
- PhD in Quantum Computing, Machine Learning, or Physics (MS with 5+ years experience)
- Expertise in quantum programming languages (Qiskit, Cirq, Q#)
- Proficiency in Python, TensorFlow/PyTorch, and quantum circuit design
- Published research in quantum machine learning or quantum information theory
- Experience with NISQ-era quantum hardware (IBM Quantum, Rigetti)
- Strong background in linear algebra, probability, and quantum mechanics
- Track record of deploying ML models at scale in production environments