Job Description
Shape the future at Nexus Labs, where we're engineering tomorrow's breakthroughs today. We're seeking an AI Research Scientist to pioneer the next wave of artificial intelligence that will define 2026 and beyond. Join our elite team of visionaries in Austin, Texas, as we develop transformative AI solutions that will revolutionize industries worldwide.
In this pivotal role, you'll collaborate with Nobel laureates and industry pioneers to design cutting-edge neural networks, quantum AI hybrids, and ethical frameworks for autonomous systems. You'll work in our state-of-the-art 'Future Lab' – a $50M facility equipped with quantum processors and neuromorphic computing arrays – to solve humanity's most complex challenges.
We offer unparalleled resources, unlimited creative freedom, and a compensation package designed to attract the world's brightest minds. If you're ready to push the boundaries of what's possible and build the AI systems of tomorrow, this is your calling.
Responsibilities
- Lead research on next-generation AI architectures including quantum neural networks and bio-inspired computing
- Develop ethical frameworks for autonomous decision-making systems that will be deployed by 2026
- Collaborate with quantum computing teams to pioneer hybrid AI-quantum algorithms
- Author breakthrough research papers for Nature and Science journals
- Mentor PhD researchers and guide cross-disciplinary innovation projects
- Partner with futurists to forecast AI's societal impact through 2030
- Design neuromorphic computing solutions for edge AI applications
Qualifications
- PhD in AI/ML, Quantum Computing, or Computational Neuroscience (or equivalent demonstrable expertise)
- Published research in top-tier journals (Nature, Science, NeurIPS) or equivalent industry breakthroughs
- Expertise in at least two of: quantum machine learning, neuromorphic engineering, or AI ethics
- Proficiency in Python, TensorFlow/PyTorch, and quantum programming languages (Q#, Qiskit)
- Track record of translating research into production systems with real-world impact
- Deep understanding of AI safety protocols and alignment challenges
- Experience with large-scale distributed computing frameworks