Job Description
We are pioneering the next era of intelligence. As part of the 2026 Horizon Initiative, we are building the foundational architectures for Artificial General Intelligence (AGI). We are seeking a visionary Lead AI Research Scientist to design scalable neural networks and redefine the boundaries of machine learning.
In this role, you won't just be writing code; you will be architecting the future of human-machine interaction. You will work with a world-class team of engineers, ethicists, and futurists to deploy safe, robust, and transformative AI systems.
Why join the 2026 Horizon Initiative?
- Shape the Future: Directly influence the roadmap for AGI deployment by 2026.
- Unmatched Resources: Access to top-tier compute clusters and proprietary datasets.
- Impact: Your work will solve complex global challenges in healthcare, energy, and logistics.
Responsibilities
- Lead the design and implementation of next-generation Transformer architectures and Reinforcement Learning algorithms.
- Define the technical roadmap for the 2026 AI product suite, ensuring scalability and efficiency.
- Collaborate with cross-functional teams to integrate ethical AI frameworks and safety protocols into core models.
- Mentor junior researchers and data scientists, fostering a culture of innovation and rigorous scientific inquiry.
- Publish high-impact research papers and present findings at leading global AI conferences.
- Optimize model inference latency and reduce computational costs for real-world deployment.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, Physics, or a related technical field.
- 10+ years of experience in machine learning research, with a strong portfolio of publications in top-tier venues (NeurIPS, ICML, ICLR).
- Deep expertise in deep learning frameworks (PyTorch, TensorFlow) and distributed computing systems.
- Proven track record of leading large-scale research projects from conception to production.
- Experience in handling massive datasets and training models on cloud infrastructure.
- Strong understanding of AI safety, interpretability, and ethical AI principles.