Who are we?👋

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.

Where you come in?

We're looking for a Senior MLOps Engineer to join our Algorithmic Underwriting team. In this role, you’ll develop and extend our MLOps system, empowering our underwriting algorithm to improve effectively and efficiently.

We'll work together across the business to tackle exciting technical challenges that go far beyond traditional MLOps systems. For instance, you’ll expand our MLOps system to manage the lifecycle of actuarial models and rules-based models alongside standard machine learning models. You’ll also have the opportunity to propose, design, and execute initiatives independently, guiding a talented team to bring these ideas to life.

We’re a commercially focused, multi-disciplinary team that brings together deep expertise in specialty insurance and scalable algorithm product development. Our squads focus on delivering high-impact features using a highly iterative, analytical approach. And we invest time in research and development, both internally and with leading academic institutions, to continually push boundaries.

What you will be doing: 🖋️

• Work with colleagues to design, deliver and evolve Ki’s end-to-end MLOps system.
• Work with colleagues to create and iterate governance processes around model lifecycle management.
• Enable colleagues across Ki to deliver models more quickly and safely into production.
• Manage overall cost and return on investment relating to the MLOps system, including build versus buy decisions and vendor selections.
• Identify opportunities to improve and extend Ki’s MLOps system.
• Advocate and uphold model management best practices.
• Act as a knowledge hub on Ki’s MLOps system, educating the rest of the Ki team on its capabilities and driving adoption across the business.
• Liaise with stakeholders to structure and evolve the roadmap for Ki’s MLOps system.
• Coaching and developing early-career members of the team.
• Drive improvements in the way we operate as a digital underwriting capability.

Requirements

• Experience with MLOps system development, including experience of applying MLOps concepts such as feature store, model registry, model monitoring.
• Experience with infrastructure as code such as terraform.
• Understanding of the control and management of data products and machine learning algorithms.
• Understanding of the importance of market compliance and core regulatory requirements.
• A Bachelor’s degree in a STEM field, or equivalent commercial experience.
• Experience with inference graphs or model workflows is a plus.
• Experience leveraging MLOps systems to productionise non-machine learning models, for example, rules-based models, is a plus.

Benefits

You’ll get a highly competitive remuneration and benefits package. This is kept under constant review to make sure it stays relevant. We understand the power of saying thank you and take time to acknowledge and reward extraordinary effort by teams or individuals.

What to expect during the recruitment process:

1. Initial recruiter screening call
2. Interview with hiring manager
3. Technical Interview (this may vary depending on the role)
4. Values Interview