Robin was established in March 2019 by CEO Richard Robinson (a former City lawyer) and CTO James Clough (a theoretical physicist who works in Machine Learning). They have since assembled a talented and diverse team of legal, software and machine learning engineers to build the next generation of contracting tools.
At Robin AI, we create groundbreaking products that are transforming legal teams. Our work is multi-disciplinary and brings together the best talent in engineering, AI and the law. Our current product uses machine learning to read and comprehend written contracts, assesses whether they adhere to our customers’ preferred positions, and then automatically amends them. But our ambitions go way beyond reviewing contracts – we want to build technology that changes the way companies all over the world do deals.
The legal industry has, thus far, been slow to embrace artificial intelligence. In part this is because the law is a naturally conservative industry, one we think is ready for disruption. But it is also because existing technology has struggled to tackle some of the unique challenges this field presents. Data is usually confidential and so datasets are limited in size. And the legal and financial stakes are high, meaning that high model accuracy and interpretability are especially important. General NLP approaches can perform poorly on legal tasks due to the unusual and precise meanings of particular words and phrases. All of these factors mean that we at Robin AI face a unique set of technical challenges that can only be tackled by creative and cross-disciplinary thinking.
As a machine learning engineer at Robin, you will be a leader in our ongoing effort to overcome these challenges, as we expand our service across different industries and contract types.
Our machine learning pipeline is written in Python using PyTorch and HuggingFace Transformers models. We also use spaCy for natural language processing and have built our own libraries for integrating with technologies used by legal teams. Models are trained and deployed on cloud services (GCP and AWS). The back-end services of our product are implemented with Python web frameworks (Django, Flask) and interact with our ML services using APIs written by the ML team.
Own and build our machine learning infrastructure - for both offline training and online inference.
Keep up to date with the latest tools, methods and research, and bring cutting edge technologies into our products.
Delve into our datasets, and understand the complex environment our products operate in, so that you can improve the way we use ML to automate challenging work.
You have experience designing, implementing and training machine learning models using a modern Python ML framework.
You write high quality, well-tested code.
You are a strong communicator who can both explain complex technical ideas to others, and can productively engage with experts in other domains to understand the technical needs of the company as a whole.
(Desirable) You have a background working in a start-up or similar sized organisation.
(Desirable) You have experience putting machine learning models into real products.
(Desirable) You have experience with modern natural language processing approaches.
You will enjoy working in a stimulating, diverse and intellectually challenging environment where collaboration is essential to achieving results.
You are comfortable managing your own schedule while achieving measurable results.
Our offices are at WeWork in Bank, where you will have a dedicated desk in our private office space, which you are free to personalize as you wish. We also have access to all of the amenities within WeWork including a pool table, table football, table tennis, co-working space, free barista-made coffee and free beer in the evenings.
£50,000 - £80,000
Meaningful equity in the business
Flexible working, mix working from home & in our London office
Focus on continual learning and development
Personal desk plant