The role focuses on researching scalable artificial intelligence and machine learning solutions with an emphasis on small language models and generative AI systems. The individual will design research that effectively transfers into real-world applications while considering constraints such as scalability, efficiency, and usability. Responsibilities include contributing hands-on to model experimentation, architecture decisions, and technical direction. The position acts as a bridge between research exploration and practical implementation. The work involves ensuring that experiments are designed with real-world constraints in mind rather than remaining purely conceptual.

Candidates must possess a strong background in applied machine learning and AI research with deep hands-on experience in Python and modern deep learning frameworks. Proficiency in PyTorch and Transformers is required. Applicants should demonstrate a strong understanding of model design, experimentation, and evaluation, alongside experience with generative AI and language models. The role requires the ability to communicate effectively with both technical and non-technical stakeholders in English. No specific degree or professional qualification is explicitly mentioned as a requirement.