Job Description
Join the Architects of the 2026 Era.
We are seeking a visionary Senior AGI Research Scientist to lead the development of the next generation of Artificial General Intelligence. At Nebula Horizon AI, we are not just predicting the future; we are building the infrastructure that will define the technological landscape of 2026 and beyond.
Our mission is to bridge the gap between narrow AI and true machine consciousness. You will work in a high-performance environment focused on large-scale model training, reinforcement learning, and ethical AI alignment. If you are passionate about pushing the boundaries of what machines can understand and reason, this is your opportunity to leave a permanent mark on human history.
Why Join Us?
- Future-Proof Your Career: Work on the core technologies that will dominate the market in 2026 and beyond.
- Unmatched Resources: Access to state-of-the-art GPU clusters and proprietary datasets.
- Elite Team: Collaborate with world-class researchers and engineers from top-tier institutions.
Don't just watch the future happen—be the one writing the code.
Responsibilities
- Model Architecture Design: Design and implement novel neural network architectures capable of zero-shot generalization and cross-modal reasoning.
- Training & Optimization: Lead the training pipelines for large-scale foundational models, optimizing for inference speed and memory efficiency.
- Research Publication: Publish high-impact research in top-tier conferences (NeurIPS, ICML, ICLR) to advance the global state of the art.
- Alignment & Safety: Develop robust alignment techniques to ensure AGI systems operate within ethical boundaries and human values.
- Mentorship: Mentor junior researchers and PhD students, fostering a culture of innovation and critical thinking.
- Technical Strategy: Contribute to the long-term technical roadmap, identifying emerging trends in AI safety and scalability.
Qualifications
- Education: Ph.D. in Computer Science, Mathematics, or a related field with a focus on Machine Learning, Deep Learning, or Cognitive Science.
- Experience: 5+ years of postdoctoral or industry experience in building large-scale deep learning models.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and experience with distributed training frameworks (Ray, MPI).
- Mathematical Maturity: Strong understanding of linear algebra, probability, and optimization theory.
- Problem Solving: Demonstrated ability to solve complex, open-ended problems in high-dimensional spaces.
- Communication: Excellent written and verbal communication skills, with the ability to translate complex technical concepts for diverse audiences.