At a Glance
- Tasks: Join our team to build cutting-edge software for algorithmic underwriting models.
- Company: Ki is revolutionising insurance with innovative technology and a diverse, agile team.
- Benefits: Enjoy competitive pay, recognition for hard work, and a focus on inclusion and diversity.
- Why this job: Be part of a fast-growing company that values creativity and challenges the status quo.
- Qualifications: Mid-senior level experience in software engineering, preferably with Python and cloud infrastructure.
- Other info: Work in a collaborative environment with opportunities for mentorship and professional growth.
The predicted salary is between 48000 - 84000 £ per year.
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 Lloyd's of London market, being 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 Ki's success – allowing us to evolve underwriting intelligently and unlock massive scale. We're 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 are 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, 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.
Senior Software Engineer, ML Ops employer: Ki
Contact Detail:
Ki Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Software Engineer, ML Ops
✨Tip Number 1
Familiarise yourself with Ki's core technologies and the specific tools they use, such as Python for server-side development and cloud infrastructure. This knowledge will help you speak confidently about how your skills align with their needs during any discussions.
✨Tip Number 2
Engage with the latest trends in machine learning and algorithmic underwriting. Being able to discuss recent advancements or case studies can demonstrate your passion and expertise in the field, making you a more attractive candidate.
✨Tip Number 3
Showcase your experience in agile methodologies, particularly Scrum or Kanban. Be prepared to share examples of how you've contributed to team ceremonies and improved processes, as this aligns with Ki's collaborative culture.
✨Tip Number 4
Network with current or former employees of Ki on platforms like LinkedIn. Gaining insights into their experiences can provide you with valuable information to tailor your approach and demonstrate your genuine interest in the company.
We think you need these skills to ace Senior Software Engineer, ML Ops
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Senior Software Engineer, ML Ops position. Tailor your application to highlight relevant experience in software engineering, particularly with Python and cloud infrastructure.
Highlight Relevant Experience: In your CV and cover letter, emphasise your experience with modern software stacks, agile methodologies, and any previous work in Fintech or Insurtech. Use specific examples to demonstrate your skills in building scalable applications and working with APIs.
Showcase Your Technical Skills: Detail your proficiency with tools and technologies mentioned in the job description, such as Git/Github, continuous integration, and automated testing. Providing concrete examples of projects where you've applied these skills will strengthen your application.
Express Your Passion for Innovation: Ki values innovation and a willingness to challenge the status quo. In your application, convey your enthusiasm for emerging technologies and your experience in developing prototypes or exploring new ideas in software engineering.
How to prepare for a job interview at Ki
✨Showcase Your Technical Skills
Be prepared to discuss your experience with server-side languages, particularly Python. Highlight any projects where you've built scalable software or worked with cloud infrastructure, as these are crucial for the role.
✨Understand Agile Methodologies
Familiarise yourself with Agile practices, especially Scrum or Kanban. Be ready to share examples of how you've participated in stand-ups, planning sessions, and retrospectives in previous roles.
✨Demonstrate Problem-Solving Abilities
Prepare to discuss how you've approached challenges in software development. Think about specific instances where you identified opportunities for growth or improvement in system architecture.
✨Emphasise Collaboration and Mentorship
Ki values teamwork and knowledge sharing. Be ready to talk about your experiences mentoring colleagues or collaborating in cross-functional teams, showcasing your ability to contribute to a diverse working environment.