Job Description
Are you ready to architect the future of artificial intelligence? Nexus Horizon Labs is seeking a visionary AI Research Scientist (2026 Horizon) to lead the charge in developing next-generation generative models and autonomous systems. In this pivotal role, you will define the technical roadmap for 2026, pushing the boundaries of what is possible in machine learning and neural architecture search.
We are not just building the future; we are defining it. You will work in a high-performance environment with top-tier talent, focusing on scalable AI solutions that will impact industries worldwide.
Responsibilities
- Lead Research Initiatives: Spearhead the development of cutting-edge algorithms for the 2026 product roadmap, focusing on Large Language Models (LLMs) and multimodal AI.
- Prototype & Deploy: Design and implement scalable deep learning pipelines, moving from research prototypes to production-ready models.
- Collaborate: Partner with cross-functional teams of engineers, product managers, and designers to translate theoretical research into practical applications.
- Mentorship: Guide a team of junior researchers and data scientists, fostering a culture of innovation and technical excellence.
- Publish & Present: Contribute to the academic community by publishing papers in top-tier conferences (NeurIPS, ICML, ICLR) and presenting at industry forums.
Qualifications
- Education: PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Experience: 5+ years of experience in research or applied machine learning, with a strong portfolio of published work.
- Tech Stack: Proficiency in Python, PyTorch, or TensorFlow, with deep knowledge of distributed computing frameworks.
- Mathematics: Strong foundation in linear algebra, calculus, probability, and statistics.
- Problem Solving: Demonstrated ability to tackle complex, open-ended problems in AI and generate innovative solutions.
- Communication: Excellent written and verbal communication skills, capable of explaining complex concepts to diverse audiences.