Join Safe Sign Technologies, a cutting-edge legal technology start-up founded at the University of Cambridge. Safe Sign aims to democratise the law for all people, equipping consumers and SMEs with robust and reliable tools to navigate legal complexity. As an AI/LLM Engineer, you will work alongside a world-leading team, innovating and delivering best-in-class technologies, often in demanding conditions and against challenging deadlines. Independent working, subject matter excellence and proactiveness are essential.

Responsibilities LLM prompt engineering (Instruction Tuning, Chain-of-thought, automated prompt Engineering) LLM training & fine-tuning (Parameter Efficient, Few-medium shot, ) Experimentation Analysis and presenting results Active study and keeping up with research literature Ability to work independently Ability to work towards an agreed goal and meet demanding deadlines Qualifications and experience Bachelor's degree in Computer Science, Engineering, Mathematics or related fields Ability to implement and verify state-of-the-art algorithms Experience running and managing experiments, analysing results and creating insights Proficiency in software development (Python, Github, Jupyer Notebooks, etc.) Proficiency with deep learning packages (such as PyTorch, Jax, or TensorFlow) Experience with ML / LLM Software packages (e.g. HuggingFace, wandb, numpy, matplotlib, NLTK, etc.) Good problem-solving and communication skills Ability to work in a dynamic and fast-paced environment Ability to demonstrate passion and knowledge in terms of relevant research topics Experience solving complex technical problems Qualifications and experience (preferred) Master's or PhD in NLP or Machine Learning First author/lead author publications at leading AI and NLP conferences (such as EMNLP, ACL, ICLR, ICML, NeuRIPS) Demonstrated projects where relevant expertise has been used for real problems Several years of experience working in this field Salary & Benefits Up to $150k/year salary Real ability to shape technical agenda and have a deep impact Mentorship and advice from top ML scientists (ex- or current DeepMind, Cambridge, UCL, Harvard) Fully remote working