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We’re on a mission to make sure everyone has access to the law.
Backed by top VC funds and a recent $40M Series A—one of Europe's five largest Series A raises of 2024—Lawhive is poised for rapid growth and expansion into the US market.
As a pioneering legal tech platform, we're seeking a Senior Research Engineer to join our mission of democratising access to the law. This role offers the opportunity to work on cutting-edge AI products, build best-in-class user experiences, and help solve one of society's most pressing problems.
We’re looking for a Research Engineer to experiment with, develop, and refine LLM-based AI assistants, document automation systems, and case workflow optimisations. This is an opportunity to bridge cutting-edge AI research and real-world applications.
- Conduct applied research on LLM-based reasoning, multi-agent systems and developing frontier bespoke models for automating legal workflows.
- Develop prototypes and experimental models to explore novel AI-driven legal solutions.
- Design and implement retrieval-augmented generation (RAG) pipelines, leveraging embeddings, vector databases, and structured retrieval techniques.
- Optimise LLM inference and fine-tuning using techniques such as LoRA, PEFT, prompt engineering, and caching.
- Integrate multi-modal and external knowledge sources to enhance AI-driven insights.
- Research and implement autonomous agentic AI systems for complex, multi-step legal workflows.
- Stay up to date with the latest advancements in model architectures, alignment and interpretability, and orchestrating complex multi-agent systems.
- Collaborate with engineers to transition experimental models into production-ready systems.
- Strong background in AI research, applied machine learning, and NLP.
- Experience with LLM model adaptation, fine-tuning, and inference optimization.
- Proficiency in Python, Pydantic, FastAPI, and working with LLM APIs (OpenAI, Anthropic, Mistral, etc.).
- Understanding of retrieval-augmented generation (RAG), vector databases, embeddings, and structured AI retrieval.
- Hands-on experience with LLM-based planning, reasoning, and autonomous task execution.
- Familiarity with self-supervised learning, reinforcement learning, or adaptive AI techniques.
- Ability to translate academic AI research into practical experiments and working prototypes.
- Experience deploying AI models in cloud environments such as AWS/GCP.
- MSc or PhD in AI, ML, Computer Science, or a related field.
✈️ 34 Holidays (25 days annual leave + your birthday off + bank hols in England)
💰 Equity (Share Options)
💰 Pension
⛳️ Regular team building activities, socials, and annual retreat!
💷 20% off legal fees through Lawhive
Lawhive London, England Office
London, United Kingdom
