LLM Research Engineer

About Robin AI

Robin AI is on a mission to revolutionize the legal industry by simplifying contracts and making law accessible to everyone. We utilize cutting-edge machine learning and contract software, enhancing traditional legal services and bringing together experts in engineering, AI, and law. Robin AI has recently raised $26m in Series B funding and has seen an impressive 5x revenue growth in the last 12 months.

About This Role

Robin AI is looking for LLM Research Engineers to join a new Research and Development function in the company. Today our product uses large language models to help automate legal work. You will work to ensure that we continue to be at the cutting edge of LLM capabilities by working on LLM fine-tuning, retrieval augmented generation, and other technologies, and by identifying new possible LLM functionality we can build into our product.

You will report directly to the CTO and co-founder as part of a small, agile and cross-functional R&D team.

This role represents an opportunity to drive the medium and long term AI roadmap for a well-funded, fast growing legal AI start-up that is now emerging as a leader in the field.

What You’ll Do

• Lead research projects aimed at improving the capabilities of the LLMs we use in our core product
• Prototype new functionality using LLMs
• Experiment with new ways our data can be used to improve the product and identify and acquire new sources of relevant data
• Be aware of and communicate the latest developments in AI
• Collaborate with our product and engineering team to help productionise the results of your research, and with partner organisations such as AWS and Anthropic
• Together with our prompt engineering team, act as a hub of expertise in LLM usage and best practice for the whole company

Qualifications

• Has exceptional ML engineering ability - evidence of which can include: Publications in top AI conferences
• Experience in ML engineering at elite AI research labs
• Experience in applied ML engineering or research in complex and high-stakes applications
• Major contributions to open source models or frameworks
• Strong experience in training, evaluating and deploying large AI models
• Experience in building products/projects using large language models (either open-source or commercial APIs)
• Deep knowledge of technical machine learning concepts, and related fields
• A scientific, hypothesis-driven mindset, and the ability to quickly build prototypes to test those hypotheses
• Adept at quickly building prototypes with Python and relevant ML frameworks
• A background working in a start-up or similar size organisation and a passion for building high-quality products
• Strong communication skills, and ability to distil technically complex concepts and data for an intelligent but non-ML audience