Lead ML Engineer

🕒 March 17

🏢🏡 London – Hybrid

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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Hiscox

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Hiscox is a leader in specialist insurance. We seek to provide the best protection and peace of mind for our clients through high quality insurance products, backed with excellent service. We are experts in covering a wide range of personal and commercial risks.

📋 Description

• Manage and grow talent: Set objectives, conduct performance reviews, and guide career progression for the MLE sub‑chapter. • Foster a strong engineering culture: Promote collaboration, psychological safety, and high standards of quality and reliability. • Provide coaching and mentorship: Support technical and professional development of Machine Learning Engineers. • Define and evolve chapter strategy: Align sub-chapter goals with chapter and organisational objectives. • Shape technical direction: Establish standards for ML engineering, deployment patterns, and MLOps. • Drive upskilling and cross‑skilling: Build capability in production ML, platform usage, and software engineering best practices. • Own and evolve the MLOps platform: Ensure it is reliable, secure, and scalable, in partnership with Group and Platform teams. • Enable scalable and reusable ML delivery: Ensure ML solutions for the business unit are deployable across value streams and efficient to operate. • Lead technical spikes and proof‑of‑concepts: De‑risk architectural decisions and explore new tools and approaches. • Ensure compliance, security, architecture, and operational standards. • Define guardrails for production ML systems: Covering deployment, monitoring, retraining, and decommissioning in collaboration with Data Science. • Partner closely with the Data Science sub-chapters and delivery team to ensure effective handover from experimentation to production. • Represent Machine Learning Engineering in strategic forums: Advocate for platforms, tooling, and scalable ML practices.

🎯 Requirements

• Bachelor’s/Master’s in Computer Science, Engineering, or a related quantitative field (or equivalent experience). • Experience as a Senior/Lead Machine Learning Engineer delivering production ML systems at scale. • Solid understanding of core data science concepts, including supervised and unsupervised learning, feature engineering, and model evaluation. • Working knowledge of statistical concepts and model evaluation techniques sufficient to review, validate, and productionise data science work. • Proven line management and/or technical mentorship of engineers; building capability and setting standards. • Demonstrated ownership of MLOps platforms or critical ML services, including CI/CD, model serving, monitoring, and incident management. • Proven ability to design, implement, and operate technical frameworks for evaluating the commercial impact of machine learning systems in production. • Effective collaboration with Data Scientists across the end-to-end ML lifecycle. • Experience working in Agile, cross-functional squads. • Insurance or financial services experience is a plus but not essential.

🏖️ Benefits

• Flexible working hours • Professional development opportunities