Job Description
Join Nexus Future Labs at the forefront of technological evolution as we pioneer solutions for 2026 and beyond. We're seeking a visionary Quantum AI Research Scientist to develop next-generation algorithms that will redefine computational boundaries. In this pivotal role, you'll collaborate with Nobel laureates and industry disruptors to transform theoretical breakthroughs into real-world applications.
Our Austin-based innovation hub offers unparalleled resources for quantum computing experimentation, including access to proprietary quantum simulators and one of the world's most powerful AI superclusters. You'll work on projects spanning quantum machine learning, neural network optimization, and autonomous system design – directly shaping technologies that will power the next decade of human progress.
Responsibilities
- Design and implement quantum-enhanced machine learning models for 2026-era autonomous systems
- Lead cross-functional research initiatives combining quantum computing with neural network architectures
- Develop novel algorithms for quantum-resistant cryptography and data security frameworks
- Collaborate with hardware engineers to optimize quantum-classical hybrid computing workflows
- Publish breakthrough research in top-tier journals and industry whitepapers
- Mentor junior researchers while maintaining cutting-edge technical expertise
- Secure patents for proprietary quantum AI methodologies
Qualifications
- PhD in Quantum Computing, Machine Learning, or Computational Physics
- 5+ years of hands-on quantum algorithm development experience
- Expertise in Python, TensorFlow/PyTorch, and quantum frameworks like Qiskit or Cirq
- Proven track record of publishing in Nature/Science or equivalent tier journals
- Deep understanding of quantum entanglement principles and error correction
- Experience with NISQ-era hardware constraints and optimization techniques
- Strong background in complex system simulation and high-performance computing
- Exceptional problem-solving skills for multi-dimensional computational challenges