Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Target Resume Now
About the Role
We are looking for an MLOps Engineer to join our Algorithmic Engineering team. In this role, you will help build and scale our MLOps system, enabling our underwriting algorithm to grow and scale. You will collaborate with colleagues across the business to solve complex technical challenges, such as generalising our MLOps system to manage actuarial and rules-based models. You will have the autonomy to propose, design, and execute innovative initiatives, delivering high-impact features as part of our forward-thinking team.
Responsibilities
- Collaborate with colleagues to design, deliver, and evolve Ki's end-to-end MLOps system.
- Empower colleagues across Ki to deliver models into production more quickly and safely.
- Identify opportunities to proactively 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 teams on its capabilities and promoting business-wide adoption.
- Support and mentor early-career members of the team.
- Champion improvements to enhance our digital underwriting capabilities.
Requirements
- Detailed knowledge of MLOps system development, including MLOps concepts such as feature stores, model registries, and model monitoring.
- Understanding of infrastructure as code using tools such as Terraform.
- Intermediate understanding of the control, management, and lifecycle of data products and machine learning algorithms.
- Understanding of the importance of market compliance and core regulatory requirements within the insurance space.
- Highly effective communication and collaboration skills to educate colleagues, act as an internal knowledge hub, and promote business-wide adoption of MLOps capabilities.
- Ability to mentor, support, and help develop early-career team members while collaborating effectively in multi-disciplined teams.
- A commercially focused approach to aligning technical MLOps initiatives with specialty insurance objectives and scalable algorithm product development.
- Knowledge of inference graphs, model workflows, or leveraging MLOps systems to productionise non-machine learning models (e.g., rules-based models) is highly advantageous.
Skills
- MLOps system development
- Feature stores
- Model registries
- Model monitoring
- Infrastructure as code
- Terraform
- Data products management
- Machine learning algorithms lifecycle management
- Market compliance
- Regulatory requirements
- Communication
- Collaboration
- Mentorship
- Leadership
- Commercial acumen
- Inference graphs
- Model workflows
Benefits
- Highly competitive remuneration and benefits package
- Package is kept under constant review to ensure relevance
- Acknowledgement and reward for extraordinary effort
About the Company
- Ki's mission is to 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.
- The Algorithmic Engineering team is a commercially focused, multi-disciplined team that combines deep expertise in specialty insurance with scalable algorithm product development to power digital underwriting.
- The team invests in iterative development and research to continuously improve the Ki platform.