GT was founded in 2019 by a former Apple, Nest, and Google executive. GT’s mission is to connect the world’s best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands.
On behalf of Kodily, GT is looking for an AI/LLM Engineer.
Kodily is a British startup that developed an AI-driven app to streamline the medical and pharmaceutical documentation review process, ensuring compliance with UK standards. Traditionally, this review process involves a multi-person team (medical, legal, and code of practice experts) and is both costly and time-consuming. After initial reviews, materials are typically sent to a UK-registered medic for final sign-off. Kodily aims to automate much of this with AI, which currently reviews text and has plans to analyze images.
Project Stage: The Kodily team has created an MVP of the product that allows for checking documents against references, relevant codes of practice, and licensing requirements. They aim to polish the MVP for the clients and release within the next 3 months.
Technical stack: It currently runs as a Streamlit dashboard coupled with a Python app on a Windows on-prem machine, using Llama-based local language models to ensure security. The plan is to create a robust web application using React/nginx, Python, and Linux.
Team: 1 Data Scientist, 1 Python engineer (part-time), business stakeholders.
Project length: Kodily is looking for full-time involvement for the first 3 months with a very high chance of extending the contract long-term.
Kodily is looking for a true LLM specialist with commercial experience of engineering an LLM backed app that has been successfully launched to solve business applications is needed to provide direction for these developments.
Develop and Test-based LLM applications that handle document review processes
Create and test LLM prompts
Create and test LLM-based logic chains
Create and test Eval logic
At least 5 years of experience in data science, AI domain
Experience working with fact-checking tools or document validation systems.
Background in backend development, particularly with cloud-based architectures (e.g., AWS, GCP, or Azure).
Familiarity with data privacy and compliance regulations in the pharmaceutical industry.
Experience contributing to research papers or publications in the AI/ML field.
client/customer LLM implementing
Strong communication skills with the ability to convey complex technical concepts to non-technical stakeholders
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