Algorithm Engineer

Look at the latest headlines and you will see something Ki insures. Think space shuttles, world tours, wind farms, and even footballers’ legs.

Ki’s mission is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days.

Ki is proudly the biggest global algorithmic insurance carrier. It is the fastest growing syndicate in the Lloyd's of London market, and the first ever to make $100m in profit in 3 years.

Ki’s teams have varied backgrounds and work together in an agile, cross-functional way to build the very best experience for its customers. Ki has big ambitions but needs more excellent minds to challenge the status-quo and help it reach new horizons.

We're looking for algorithm engineers to join our Algorithm Engineering team. You will work at the intersection of underwriting and algorithm development, developing machine learning enabled products that operate across over 25 classes of business ranging from Commercial Properties to Oil Rigs to Event Contingency insurance.

You will help us better evaluate every single risk on its own merits, and on how it helps us build a profitable and stable portfolio, all in the space of under a minute. From large scale geospatial analysis to manage our exposure to natural catastrophes to research and development on low data volume machine learning approaches for classes of business with very few claims (like Terrorism insurance!). We operate at the point where the two very different worlds of technology and specialty insurance meet, and you will be part of both.

We're a multi-disciplined team and pride ourselves on being commercially focused, bringing together deep expertise in specialty insurance and scalable machine learning product development. Our squads focus on delivering high-impact features and we favour a highly iterative, analytical approach. We invest time in research and development, internally and with academic institutions.