Job Description
Shape the future of artificial intelligence at NeuralHorizon Labs. As we approach 2026, we're pioneering breakthroughs in quantum-entangled neural networks and AGI safety protocols. Join our elite research team in Austin, Texas, where your work will directly influence the trajectory of human-machine collaboration. We offer state-of-the-art facilities, unparalleled computational resources, and a culture that celebrates intellectual curiosity.
This role is perfect for visionary researchers who thrive at the intersection of theoretical mathematics and practical implementation. You'll collaborate with Nobel laureates and industry disruptors while contributing to projects that will define the next decade of technological advancement. Our compensation package includes equity, flexible work arrangements, and dedicated R&D funding.
Responsibilities
- Design and implement novel quantum machine learning algorithms for 2026-era computational paradigms
- Lead cross-functional teams in developing ethical AI frameworks for autonomous systems
- Author peer-reviewed publications in top-tier AI conferences (NeurIPS, ICML, ICLR)
- Prototype and validate next-gen neural architectures using 10,000+ GPU clusters
- Collaborate with quantum computing teams to optimize hybrid AI-quantum workflows
- Develop safety protocols for superintelligent systems with alignment-focused research
- Mentor PhD researchers and shape the next generation of AI thought leaders
- Secure federal and private funding for frontier AI research initiatives
Qualifications
- PhD in Computer Science, Mathematics, or Physics with 5+ years of ML research experience
- Published record in top-tier AI/ML conferences (NeurIPS, ICML, ICLR)
- Expertise in transformer architectures, reinforcement learning, and generative models
- Proficiency in PyTorch, TensorFlow, and distributed computing frameworks
- Deep understanding of quantum computing principles and quantum machine learning
- Experience with large-scale model training (10B+ parameter models)
- Demonstrated ability to translate theoretical concepts into production-ready systems
- Strong background in AI safety, alignment research, and ethical frameworks