Job Description
Join Nexus Labs at the forefront of 2026's technological revolution as a Quantum AI Research Scientist. We're pioneering the intersection of quantum computing and artificial intelligence to solve humanity's most complex challenges. In this role, you'll develop next-gen algorithms that leverage quantum supremacy for real-world applications in cryptography, optimization, and machine learning. Our Austin-based innovation hub offers unparalleled resources, including a 128-qubit quantum processor and collaboration with MIT's Quantum Engineering Center.
We value intellectual curiosity and disruptive thinking. You'll work in a cross-functional team of Nobel laureates, quantum physicists, and AI specialists to publish breakthrough research and patent foundational technologies. Your contributions will directly shape the future of computational science while enjoying competitive equity packages and flexible R&D time.
Responsibilities
- Design and implement quantum machine learning algorithms for 2026-era applications
- Develop hybrid quantum-classical computing architectures for enterprise-scale problems
- Lead research initiatives in quantum neural networks and error correction
- Collaborate with hardware teams to optimize quantum circuit designs
- Author peer-reviewed publications and present at IEEE Quantum Computing Summit
- Mentor junior researchers in quantum programming frameworks (Qiskit, Cirq)
- Secure $2M+ in annual R&D funding through NSF and DoE grants
Qualifications
- PhD in Quantum Computing, Physics, or Computer Science (or equivalent experience)
- 3+ years of hands-on quantum algorithm development with 50+ qubit systems
- Published research in Nature/Science on quantum machine learning
- Expertise in Python, C++, and quantum programming languages
- Deep understanding of quantum error correction and fault tolerance
- Track record of securing government or corporate research grants
- Experience with superconducting and photonic quantum hardware
- Strong background in tensor networks and quantum simulation