Applied Machine Learning Engineer, Deep Science Ventures

• Machine learning practitioner who thrives on the question of how to make users superhuman by continually optimising models
• Has worked in fast moving start-up environments from early 10s of users to hundreds of thousands of users
• Up to speed with state-of-the-art in transformers and particularly Large Language Models with strong opinions and ideally practical experience in embedding, LLM-based reasoning/classification, vector databases, semantic search, retrieval strategies and making LLM interfaces fast enough for scale
• Experience with fine-tuning and model optimisations (for performance and inference speed/cost)
• Comfortable leveraging managed services for fast prototyping
• Ability to learn – you learn new concepts and skills rapidly and look to understand things in an in-depth way
• Confident in designing analytics pipelines to track and optimise user performance and the impact of changes to the model

Desirable

• Design, train and deploy custom transformer-based large language models to accelerate the speed of scientific discovery based on our existing tried and tested venture design approaches
• Design and evaluate model performance and accuracy metrics relevant to speed and quality of scientific discovery and product development
• Lead data strategy integration across internal sources (including text, video and audio data) and external sources and products
• Building systems to continually fine-tune leveraging human experience to continually improve the effectivness of the model
• Auto-generate into external communication material