Job Description
Shape the future at Nexus Labs! We're pioneering the intersection of quantum computing and artificial intelligence to solve humanity's most complex challenges by 2026. As a Quantum AI Research Engineer, you'll architect next-generation algorithms that leverage quantum supremacy for breakthroughs in materials science, climate modeling, and drug discovery. Join our elite team of futurists in Austin's thriving tech corridor, where your work will directly impact the next wave of technological revolution.
We offer unparalleled resources—including access to quantum hardware simulators, cutting-edge AI frameworks, and a culture of relentless innovation. Your ideas will fuel projects that redefine what's possible in computing, with opportunities to publish groundbreaking research and collaborate with Nobel laureates.
Responsibilities
- Design and implement hybrid quantum-classical AI algorithms for optimization and machine learning tasks
- Develop error-corrected quantum circuits for high-stakes computational problems
- Lead cross-functional projects combining quantum physics, neural networks, and probabilistic modeling
- Create simulation frameworks for quantum AI applications in healthcare and energy sectors
- Author peer-reviewed publications and patents for novel quantum AI methodologies
- Mentor junior researchers and contribute to our open-source quantum AI toolkit
- Collaborate with hardware teams to bridge theoretical models with quantum processors
Qualifications
- PhD in Quantum Computing, Computer Science, or Physics (or equivalent experience)
- Expertise in quantum programming languages (Qiskit, Cirq) and AI frameworks (PyTorch, TensorFlow)
- Published research in quantum machine learning or quantum algorithms
- Proficiency in high-performance computing and cloud quantum platforms (IBM Quantum, Amazon Braket)
- Strong mathematical background in linear algebra, probability theory, and quantum mechanics
- Experience with quantum error correction and fault-tolerant systems
- Track record of translating theoretical concepts into practical implementations