We are looking for a confirmed/senior Machine Learning Engineer to help us build the first legal AI platform.
You’ll join the “Scribe” team with a clear mission: revolutionize legal drafting (Drafting) in France, Italy, and Germany. We deploy cutting-edge solutions (LLMs) directly where lawyers and legal professionals work.
Your roadmap (3–6 months):
Web App: Build a multi-document drafting tool and a dedicated chatbot.
Integrations: Launch add-ins to assist daily legal drafting.
AI & Translation: Enhance our automatic PDF translation features.
Our web tech stack is based on NodeJS, NestJS, React & NextJS.
Missions 🛠
- Develop NLP models (whether based on Machine Learning or not) to assist with information search and recommendation within legal documents, in particular.
- Maintain and monitor these models in production.
- Design conversational agents to accelerate lawyers’ work across various areas of law, ensuring accurate responses and facilitating drafting tasks.
- Collaborate with different types of profiles, including engineers, product managers, and product designers, to identify new product development opportunities.
- Participate in internal knowledge sharing and consolidation of best practices; contribute to the development of our Engineering strategy.
Ideal Profile 👀
- Strong knowledge of Machine Learning (both classical and deep learning) for data extraction and recommendation, ideally with some first-hand experience with LLMs.
- Experience with natural language search engines and inverted indexes such as Elasticsearch.
- Solid understanding of MLOps challenges, with a strong motivation to grow in this area.
- A keen interest in artificial intelligence topics.
- Desire to identify, analyze, and deploy the latest scientific advances in production.
- Strong Python development skills, with a focus on algorithm design.
- Proficiency in French, as you will be working with legal data in French.
Extras of the role 👁
- Like all engineers at Doctrine, you will join one of our cross-functional chapters — in this case, the Web chapter. Within this chapter, you will contribute to internal projects aimed at improving our processes and shaping our long-term vision. The chapter meets every week to:
- Share knowledge: keep track of the state of the art, review scientific papers, continuous improvement, best practices, etc.
- Propose improvements: experiment with new tools, suggest new processes to implement.
- You will also take part in recruitment: all individual contributors meet candidates through technical assessments or interviews.