Level

Hiscox

Machine Learning Engineer

Hiscox is hiring a Machine Learning Engineer. Level rates it ; you can apply on Hiscox.

Level's read on this job

  • On Level's scale, this machine learning engineer role is Builds AI ●●●●: the job is building AI systems.
  • Tools and skills the posting cites include Databricks.
  • Level lists 85 other open roles at Hiscox.
  • The role was posted in the last few days.

AI in this role

databricks

Job Type:

Permanent

Build a brilliant future with Hiscox
 

About Hiscox


Hiscox UK is a leading brand in the insurance market, recognised as setting the standards others try to emulate. We consistently deliver strong growth and exceptional returns, recruiting only the very best and empowering them to deliver. We are known for insuring the homes of the rich and famous through to the most innovative technology companies. Our customers are diverse and unique and are only united by our ability to provide specialist insurance tailored to their needs.


The Team


The Hiscox UK Data Science team operates across the UK business unit, providing data-driven insights that inform strategic decision-making and operational improvements. We specialise in machine learning and generative AI solutions to address complex business challenges in collaboration with stakeholders across the business. We deliver robust, scalable models and analytical solutions that drive innovation and support evidence-based decisions.



The Role


We’re looking for a talented and pragmatic Machine Learning Engineer to join our growing data science team. We’re working on a wide range of greenfield projects, from fraud detection to generative AI, giving you the chance to help shape solutions from the ground up. You’ll be shaping the full machine learning lifecycle, collaborating closely with data scientists and engineers in a cross-functional environment to define how we solve problems with data science. This role is key to ensuring that models developed in research are successfully transitioned into scalable, production-ready solutions.


This role is suited to individuals who are passionate about data and committed to software engineering best practices, with a drive to innovate and advance organisational capabilities. 


Key Responsibilities


  • Contribute to the design and evolution of our Data Science platform, helping define best practices, tooling and the ML Engineering function as the team and project portfolio grow.
  • Have a strong voice in the automation of the end-to-end data science lifecycle, leveraging CI/CD and infrastructure as code to support scalable, enterprise-grade production workflows.
  • Work closely as a team, collaborating on all aspects of the data science and deployment lifecycle across traditional ML and generative solutions.
  • Work collaboratively with dependency teams including data engineers, software engineers and business stakeholders.
  • Write high quality python code following industry best practice for model development, deployment and maintainability.
  • Contribute technically to the data science modelling and project workflows, helping select modelling approaches, participating in architecture discussions, and deployment strategies.

Candidate Profile


Skills and experience:


  • Proven track record in data science or ML engineering roles within a business setting
  • Strong python programming skills and wider software engineering best practice
  • Strong communication skills including translation of technical concepts for non-technical stakeholders
  • Good understanding of core data science principles
  • Experience with production-level cloud-native deployment of machine learning services, using containerisation, Kubernetes or equivalent. We work across an Azure and Databricks estate, therefore experience with these platforms would be particularly beneficial
  • Utilisation of an industry-standard software stack for data and software, including VCS (git), CI/CD (Azure DevOps desirable) and Project Management (JIRA)
  • Experience deploying data science models to solve real-world business problems in production, ideally within a regulated industry such as finance or insurance
  • Experience utilising LLMs, generative or agentic AI in a commercial setting is beneficial

Why Join Us?


A career at Hiscox is more than just a job—it’s an opportunity to grow, thrive, and be rewarded for your contribution. Beyond a competitive salary, we offer a comprehensive benefits package designed to support your financial, physical, and personal wellbeing. From retirement plans and healthcare coverage to flexible working options and professional development support, we aim to create an environment where you can succeed both inside and outside of work.


To explore the full range of benefits available in your location, visit: Benefits | Hiscox Group


We also know that none of us ever stops learning. Whether you’re just starting out or have decades of experience, we’ll give you the tools and opportunities to nurture your talent and fulfil your potential. Our learning and development programmes include financial support for professional qualifications, world-class technical training, and a wide range of courses focused on personal growth, career progression, and leadership skills.


Diversity and Hybrid working
 

At Hiscox we care about our people. We hire the best people for the job and we’re committed to diversity and creating a truly inclusive culture, which we believe drives success. We operate a hybrid working model, set by the team rather than the business, to enable you to manage your own personal work-life balance. We see it as the best of both worlds; structure and sociability on one hand, and independence and flexibility on the other


Work with amazing people and be part of a unique culture

How we rate this

Machine Learning Engineer at Hiscox rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Databricks

Also common in machine learning engineer jobs at this level

Pay

Typical machine learning engineer job
$198k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

  1. What's a project where you used Databricks hands-on?
  2. How would you decide a model or AI system is ready to ship?
  3. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: Databricks. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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