Job Description
We are pioneering the technology landscape for 2026 and beyond. Nexus Horizon is seeking a visionary Senior AI Research Scientist to lead our cutting-edge research in Generative AI and Multimodal Large Language Models.
In this pivotal role, you will architect the next generation of artificial intelligence systems, pushing the boundaries of what is possible in automated reasoning, creative generation, and autonomous agents. You will work in a high-performance environment, collaborating with world-class engineers and ethicists to ensure our AI solutions are not only powerful but responsible.
Why Join Us?
- Shape the future of technology.
- Competitive compensation and equity package.
- State-of-the-art computing infrastructure.
If you are passionate about solving complex problems and defining the trajectory of AI for the coming decade, we want to hear from you.
Responsibilities
- Lead Research Initiatives: Define and execute the research roadmap for Generative AI models targeting deployment in 2026.
- Model Architecture: Design, train, and optimize deep learning architectures for high-performance natural language processing and computer vision tasks.
- Publish & Patent: Author high-impact research papers for top-tier conferences (NeurIPS, ICML, ICLR) and secure patents for proprietary algorithms.
- Team Leadership: Mentor junior researchers and data scientists, fostering a culture of innovation and scientific rigor.
- Collaboration: Partner with engineering teams to translate theoretical research into scalable production-ready APIs.
- Ethical AI: Advocate for and implement fairness, transparency, and safety guidelines within model training pipelines.
Qualifications
- Education: PhD in Computer Science, Mathematics, Statistics, or a related field.
- Experience: 5+ years of industry experience in AI/ML research or a comparable academic research track record.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow; deep understanding of transformer architectures and reinforcement learning.
- Programming: Strong coding skills with a focus on performance optimization and distributed training.
- Communication: Excellent written and verbal communication skills for technical documentation and stakeholder presentations.
- Problem Solving: Demonstrated ability to tackle ambiguous, unsolved problems in the field of Artificial General Intelligence (AGI).