Job Description
Are you ready to define the trajectory of Artificial General Intelligence? Nexus Horizon Labs is seeking a visionary Senior AGI Research Scientist to lead the charge in building the cognitive architectures of tomorrow. We are not just building software; we are architecting the future of human-machine collaboration by 2026 and beyond.
In this pivotal role, you will work at the intersection of theoretical computer science, advanced machine learning, and cognitive neuroscience. You will design and implement next-generation neural frameworks capable of reasoning, planning, and adapting to complex, real-world scenarios. If you are passionate about solving the hardest problems in AI and have a track record of pushing the boundaries of what is possible, we want to hear from you.
Responsibilities
- Architect Next-Gen AI: Design and implement novel deep learning architectures specifically tailored for Artificial General Intelligence (AGI) capabilities.
- Research Leadership: Lead high-impact research initiatives focused on reasoning, multi-modal understanding, and long-term planning in AI systems.
- Safety & Alignment: Develop and implement safety protocols and ethical frameworks to ensure AI systems remain robust, transparent, and aligned with human values.
- Model Optimization: Drive the optimization of large-scale model training, inference efficiency, and resource utilization.
- Collaboration: Collaborate cross-functionally with engineering, product, and design teams to translate cutting-edge research into scalable products.
- Publication: Author and publish high-impact papers in top-tier AI conferences (NeurIPS, ICML, ICLR) to establish thought leadership in the field.
Qualifications
- Education: Ph.D. in Computer Science, Artificial Intelligence, or a related field from a top-tier institution.
- Experience: Minimum of 5-7 years of progressive experience in research and development within the AI/ML space.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and experience with distributed training systems (e.g., Ray, DeepSpeed).
- Domain Knowledge: Deep understanding of Large Language Models (LLMs), Transformers, and reinforcement learning.
- Creativity: Proven ability to think outside the box and generate innovative solutions to complex algorithmic problems.
- Communication: Exceptional written and verbal communication skills, with the ability to articulate complex technical concepts to diverse audiences.