Staff Algorithm Engineer

Ki Insurance
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist - Optimisation

Applied Machine Learning Engineer

Staff Data Scientist

Data Scientist/ Software Engineer

Senior Data Scientist

Senior Data Scientist

Purpose of the Job:

Who are we?

Ki is the biggest global insurance tech company you’ve never heard of, unless you’ve been looking to insure a satellite, wind farm or music festival recently.

We launched in 2021 on the back of a fund-raise that delivered $500m of investment, making us one of the largest fintech start-ups that year. Our investors were excited about the fact we were revolutionising the way a 333 year-old industry was working. We wrote over $400m worth of premium in 2021, doubled in size over 2022, and have continued to grow through 2023. There are very few industries left that are mainly paper based, but the specialty insurance market is one. Together with partners at Google and UCL, we developed Ki and created a platform that helps insurance brokers place risk in a fast and frictionless way. We’re continuing to lead the charge on the digitisation of this market and we need more excellent minds to work with us to realise this goal and create more opportunities.

What you will be working on:

This is an exciting opportunity to join the only digital syndicate on our journey of growth, where you’ll join us as a Staff Algorithm Engineer within our Algorithmic Underwriting team. You’ll 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.

We focus on the commercial outcomes that our algorithm achieves, and we like (who doesn’t?) well tested and maintainable code. Our algorithm is built in Python and our infrastructure is entirely cloud native and we maintain our infrastructure as code.

If you are looking for a role where you will drive, design, develop and maintain algorithms to carry out algorithmic underwriting and digital portfolio management activities at scale, whilst working with leadership to design and own Algorithmic Underwriting’s risk and control processes, then this could be the role for you.

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.

If this sounds like a role and a culture that appeals to you, let us know.

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.