AI LLM Engineer

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June 19

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Safe Sign Technologies

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We're building the next-generation, reference LLM for Law - to solve the AI trust problem and make high-quality, reliable legal advice accessible to all. World-leading Cambridge, Oxford and Harvard team.

11 - 50 employees

📋 Description

• Join Safe Sign Technologies, a cutting-edge legal technology start-up founded at the University of Cambridge. • 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. • Responsibilities include LLM prompt engineering, LLM training & fine-tuning, experimentation analysis and presenting results, active study and keeping up with research literature, ability to work independently, and ability to work towards an agreed goal and meet demanding deadlines.

🎯 Requirements

• 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, Jupyter 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 • Master's or PhD in NLP or Machine Learning (preferred) • First author/lead author publications at leading AI and NLP conferences (such as EMNLP, ACL, ICLR, ICML, NeuRIPS) (preferred) • Demonstrated projects where relevant expertise has been used for real problems (preferred) • Several years of experience working in this field (preferred)

🏖️ Benefits

• 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