Hiscox
Insurance
PrincipalMachineLearningEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Principal Machine Learning Engineer at Hiscox. Skills: Machine Learning Engineering, MLOps, Production ML systems. Act as technical lead for Machine Learning Engineering. Technically lead complex ML systems”
Industry & Context.
Troubleshooting; Root cause analysis
What They're Looking For.
Must Have
Bachelor’s or Master’s degree in Computer Science, Engineering, or related quantitative field (or equivalent experience), Extensive experience as senior or principal Machine Learning Engineer delivering production ML systems at scale, Proven track record of owning or shaping ML platforms, MLOps frameworks, or critical ML infrastructure, Exceptional Python skills in machine learning engineering context, Software engineering fundamentals (OOP, testing, design patterns), Deep experience building, deploying, and operating production ML systems, Hands-on experience with major cloud platform (AWS, GCP, or Azure), Containerised deployments, Expert knowledge of MLOps and CI/CD, Working knowledge of SQL, Experience using AI-assisted coding tools in production engineering context
Nice to Have
Insurance or financial services experience
What You'll Do.
Act as technical lead for Machine Learning Engineering
Technically lead complex ML systems
Define and evolve production ML patterns
Lead deep technical decision-making
Contribute hands-on to critical systems
Define best practices for AI-assisted coding tools
Lead by example applying AI-assisted development techniques
Partner with teams to design
Shape platform standards and interfaces
Lead technical spikes and proof-of-concepts
Influence developer tooling choices
Ensure platform enables fast
Ensure ML systems meet standards
Define and implement frameworks for monitoring
Champion operational excellence across ML services
How You'll Work.
Team & Collaboration
Cross-functional environments; Data Science teams; Engineering teams; Platform teams; Value streams
Process & Methodology
CI/CD, Agile
Full Job Description
_**Job Type:**_ Permanent **Build a brilliant future with Hiscox** **Principal Machine Learning Engineer** **Location:** London/York **Why Hiscox London Market** Hiscox London Market sits at the centre of global specialist insurance, tackling some of the most complex and unusual risks in the world. These are not commoditised problems, they demand deep expertise, strong judgement, and increasingly, sophisticated data and machine learning capabilities. We have a strong track record of putting AI into real production use, from augmenting underwriting decisions to shaping future market standards through partnerships and market‑first innovation. This is an environment where advanced ML systems are expected to operate reliably, safely, and at scale, not remain in experimentation. You’ll join a culture that values technical excellence, ownership, and courage, where senior individual contributors are trusted to set direction, challenge thinking, and build platforms that matter. For a Principal Machine Learning Engineer, this is a chance to work on high‑impact ML systems, influence how AI is adopted across the London Market, and help shape the future of insurance. **Role Purpose** As a **Principal Machine Learning Engineer (MLE)** , you bring a wealth of experience in building, scaling, and operating production machine learning systems, and use that experience to provide deep technical leadership across machine learning engineering and MLOps. You play a key role in shaping the architectural strategy for production ML systems and the ML Platform, working closely with Data Science, Engineering, and Platform teams to define patterns, standards, and tooling that enable reliable, repeatable delivery at scale. Through hands‑on contribution, design leadership, and technical mentorship, you help teams navigate complex technical decisions and build robust, maintainable systems. A central focus of the role is enabling the organisation to move quickly without sacrificing quality, evolv
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