Job Description
Join Nexus Labs at the forefront of technological evolution as we pioneer breakthroughs in quantum AI systems. We're seeking visionary researchers to develop next-generation algorithms that will redefine computational boundaries by 2026. Our interdisciplinary team collaborates with MIT, Stanford, and NASA to transform theoretical concepts into scalable solutions for climate modeling, drug discovery, and autonomous systems.
As a cornerstone of our Quantum AI division, you'll access state-of-the-art labs in our LEED-certified headquarters and participate in exclusive partnerships with D-Wave and IBM Quantum. We offer equity grants, unlimited learning stipends, and flexible remote work options while maintaining our commitment to in-person collaboration.
Responsibilities
- Design and implement quantum machine learning models for complex optimization problems
- Lead cross-functional R&D initiatives combining quantum computing, neural networks, and predictive analytics
- Develop patent-pending algorithms for real-time data processing at quantum scale
- Collaborate with hardware teams to optimize quantum-classical hybrid systems
- Present findings at premier conferences (Q2B, IEEE Quantum Week) and publish in Nature Physics
- Secure $1M+ in annual research grants through NSF and DARPA proposals
Qualifications
- PhD in Quantum Computing, Theoretical Physics, or Machine Learning with 3+ years industry experience
- Published research in quantum algorithms or quantum neural networks (arXiv/IEEE/ACM)
- Proficiency in Qiskit, Cirq, or Q# frameworks with GitHub portfolio demonstrating quantum implementations
- Experience with variational quantum eigensolvers (VQE) or quantum approximate optimization (QAOA)
- Deep understanding of quantum error correction and fault-tolerant architectures
- Track record of translating theoretical quantum concepts into practical prototypes