Job Description
Join Nexus Labs at the forefront of technological evolution as we pioneer the convergence of quantum computing and artificial intelligence. We're seeking a visionary Quantum AI Integration Engineer to architect next-generation systems that will redefine computational boundaries. This role offers unparalleled opportunities to work with cutting-edge hardware and algorithms in a dynamic, research-driven environment.
Our Austin campus features state-of-the-art quantum labs and collaborative innovation spaces. As part of our elite FutureTech Division, you'll collaborate with Nobel laureates and industry pioneers to develop solutions for climate modeling, drug discovery, and autonomous systems. We offer competitive equity packages, unlimited learning stipends, and flexible work arrangements.
Responsibilities
- Design and implement hybrid quantum-classical AI architectures for complex optimization problems
- Develop error-correction protocols for quantum neural networks
- Create integration frameworks between quantum processors and classical machine learning pipelines
- Lead cross-functional teams in prototyping quantum-enhanced AI applications
- Research and implement novel algorithms for quantum advantage in ML workflows
- Optimize quantum circuit designs for specific AI model architectures
- Document technical specifications and contribute to open-source quantum AI initiatives
Qualifications
- PhD in Quantum Computing, Computer Science, or related field (MS with exceptional experience considered)
- 3+ years of hands-on experience with quantum programming frameworks (Qiskit, Cirq, or PennyLane)
- Expertise in machine learning frameworks (PyTorch, TensorFlow) and high-performance computing
- Strong background in quantum error correction and fault-tolerant systems
- Published research in quantum machine learning or AI integration
- Proficiency in Python, C++, and quantum circuit design
- Demonstrated experience with cloud quantum platforms (IBM Quantum, Amazon Braket)
- Ability to translate complex quantum concepts into practical AI solutions