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Job Details: Senior Software Engineer, ML Ops
Vacancy Name:Senior Software Engineer, ML Ops
Employment Type:Permanent
Location:London
Role Details
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 and the fastest growing syndicate in the Lloyds 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.
What’s the role?
Our broker platform is the core technology to Kis success – allowing us to evolve underwriting intelligently and unlock massive scale. Were a multi-disciplined team, bringing together expertise in software and data engineering, full stack development, platform operations, algorithm research, and data science. Our squads focus on delivering high-impact features – we favour a highly iterative, analytical approach. Initially, you would be working as part of the core technology group in the model ops squad. The Model Ops squad is focused on enabling Ki to build and deploy best-in-market algorithmic underwriting models and graphs of models at scale. Sample products you might be involved in building include developer tooling, microservice orchestration systems, ML model serving infrastructure, and feature serving and storage infrastructure.
Principal Accountabilities
- Build robust and scalable software for business critical, web-based applications.
- Design, build, test, document and maintain APIs and integrations.
- Ensure quality control using industry standard techniques such as automated testing, pairing, and code review.
- Document technical design and analysis work.
- Assess current system architecture and identify opportunities for growth and improvement.
- Build mock-ups or prototypes to explore and troubleshoot new initiatives.
- Explore new ideas and emerging technologies, develop prototypes quickly.
- Uphold and advance the wider engineering team’s principles and ways of working.
- Serve as a domain expert for one or more of Ki’s core technologies.
- Mentor and coach colleagues in both engineering and business domain subjects.
Required Skills and Experience
- Experience as a mid-senior level engineer working across a modern stack.
- Strong software engineering principles (SOLID, DRY, data modelling).
- Professional experience with a server-side language, ideally Python.
- Comfortable working with cloud infrastructure, infrastructure as code, familiar with standard logging and monitoring tools used to investigate issues.
- Experience with continuous integration, or ideally, continuous delivery.
- Strong familiarity with build tools and version control tools (e.g. Git/Github).
- Experience working in agile teams, following Scrum or Kanban, participating in regular ceremonies including stand-ups, planning, and retrospectives.
- Previous experience of software development in the financial markets, Fintech or Insurtech is preferable.
- Experience or interest in building developer tooling, platform engineering, and/or machine learning is desirable.
Our culture
Inclusion & Diversity is at the heart of our business at Ki. We recognise that diversity in age, race, gender, ethnicity, sexual orientation, physical ability, thought and social background bring richness to our working environment. No matter who you are, where you’re from, how you think, or who you love, we believe you should be you.
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.
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