Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join us to develop cutting-edge AI solutions for legal workflows and enhance user experiences.
- Company: Lawhive is a pioneering legal tech platform on a mission to democratise access to the law.
- Benefits: Enjoy 34 holidays, equity options, a pension, and fun team-building activities.
- Why this job: Be part of a rapidly growing company making a real social impact in the legal field.
- Qualifications: Strong AI research background, proficiency in Python, and experience with LLMs required.
- Other info: Opportunity to work on innovative projects backed by top VC funding.
The predicted salary is between 48000 - 84000 £ per year.
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 are 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.
Responsibilities:- 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 holidays in England)
- Equity (Share Options)
- Pension
- Regular team building activities, socials, and annual retreat!
- 20% off legal fees through Lawhive
Senior AI Research Engineer employer: Lawhive
Contact Detail:
Lawhive Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI Research Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in AI research, particularly in LLMs and multi-agent systems. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Showcase your hands-on experience with relevant technologies like Python, FastAPI, and LLM APIs. Consider preparing a portfolio of projects that demonstrate your skills in developing AI-driven solutions, as this can set you apart from other candidates.
✨Tip Number 3
Network with professionals in the legal tech and AI fields. Attend industry events or webinars where you can meet potential colleagues and learn more about the challenges they face, which can give you insights to discuss during your interview.
✨Tip Number 4
Prepare to discuss how you can bridge the gap between academic research and practical applications. Think of examples where you've successfully translated complex AI concepts into real-world solutions, as this aligns perfectly with the role's responsibilities.
We think you need these skills to ace Senior AI Research Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in AI research, machine learning, and NLP. Focus on relevant projects, especially those involving LLM model adaptation and fine-tuning, to demonstrate your suitability for the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for democratising access to the law and how your skills align with Lawhive's mission. Mention specific experiences that relate to developing AI-driven legal solutions and your understanding of retrieval-augmented generation.
Showcase Relevant Projects: Include a section in your application that showcases any relevant projects or prototypes you've worked on. Highlight your hands-on experience with LLM-based planning, reasoning, and any cloud deployment of AI models.
Highlight Continuous Learning: Demonstrate your commitment to staying updated with the latest advancements in AI by mentioning any recent courses, workshops, or conferences you've attended. This shows your dedication to the field and your ability to bring fresh insights to the team.
How to prepare for a job interview at Lawhive
✨Showcase Your AI Knowledge
Make sure to highlight your understanding of AI research, particularly in LLMs and NLP. Be prepared to discuss specific projects you've worked on that demonstrate your expertise in these areas.
✨Demonstrate Problem-Solving Skills
Prepare examples of how you've tackled complex problems using AI solutions. Discuss your approach to developing prototypes and experimental models, especially in legal contexts.
✨Familiarise Yourself with RAG Techniques
Since the role involves retrieval-augmented generation, brush up on your knowledge of RAG pipelines and vector databases. Be ready to explain how you would implement these techniques in real-world applications.
✨Discuss Collaboration Experience
Collaboration is key in this role. Share experiences where you've worked with engineers or cross-functional teams to transition models into production-ready systems, highlighting your communication skills.
