Job Description
Join Nexus Labs at the forefront of technological evolution as we pioneer quantum-AI hybrids that will redefine industries by 2026. We're seeking a visionary Quantum AI Research Scientist to architect next-gen computational systems that merge quantum mechanics with artificial intelligence. This role offers unparalleled opportunities to shape humanity's digital future in our state-of-the-art San Francisco lab, where breakthroughs in quantum neural networks, superposition-based machine learning, and error-corrected AI are accelerating daily.
You'll collaborate with Nobel laureates and Turing Award winners to develop proprietary quantum algorithms that solve previously impossible computational challenges. Our interdisciplinary teams work on high-impact projects including climate modeling, drug discovery acceleration, and financial market prediction systems that will power the 2026 tech ecosystem.
Responsibilities
- Design and implement quantum-AI hybrid architectures for exponential computational acceleration
- Lead development of error-corrected quantum neural networks achieving 1000x classical performance
- Pioneer superposition-based machine learning algorithms for 2026-era data processing
- Collaborate with hardware teams to optimize quantum-AI co-design protocols
- Author breakthrough research published in Nature/Science and industry-leading journals
- Mentor cross-functional teams in quantum machine learning principles
- Secure $10M+ in research grants for quantum-AI initiatives
Qualifications
- PhD in Quantum Computing, AI, or Computational Physics with 5+ years industry experience
- Published research in quantum machine learning or quantum information theory
- Expertise in quantum programming frameworks (Qiskit, Cirq, PennyLane)
- Deep understanding of quantum error correction and fault tolerance protocols
- Proven track record of translating theoretical concepts to scalable implementations
- Experience securing federal research grants or venture capital for quantum projects
- Proficiency in Python, C++, and quantum circuit optimization techniques