Job Description
Join Nexus Quantum Labs at the forefront of computational revolution as we pioneer quantum machine learning solutions for 2026 and beyond. We're seeking visionary engineers to develop hybrid quantum-classical algorithms that solve previously impossible problems in drug discovery, climate modeling, and AI optimization. Our Austin-based R&D hub offers state-of-the-art quantum hardware, collaborative innovation labs, and unparalleled opportunities to shape the future of technology.
Why Nexus Quantum Labs?
- Cutting-edge quantum computing infrastructure
- Collaborative research environment with Nobel laureates
- Competitive equity packages and comprehensive benefits
- Direct impact on breakthrough scientific applications
Responsibilities
- Design and implement quantum machine learning algorithms on hybrid quantum-classical systems
- Optimize quantum circuits for NISQ-era hardware limitations
- Develop novel error mitigation techniques for quantum neural networks
- Collaborate with cross-functional teams to integrate quantum solutions into real-world applications
- Lead research publications in top-tier quantum computing conferences
- Mentor junior researchers and contribute to quantum software development roadmap
- Stay current with emerging quantum ML frameworks and hardware advancements
Qualifications
- PhD in Quantum Computing, Machine Learning, or related field (MS with 3+ years experience)
- Expertise in quantum programming languages (Qiskit, Cirq, PennyLane)
- Proficiency in Python, TensorFlow/PyTorch, and high-performance computing
- Published research in quantum machine learning or quantum algorithms
- Experience with quantum error correction and noise mitigation strategies
- Familiarity with quantum hardware platforms (IBM Quantum, Rigetti, IonQ)
- Demonstrated ability to translate complex theoretical concepts into practical implementations
- Strong problem-solving skills and passion for quantum innovation