Lead Machine Learning Engineer

🕒 March 31

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Zego

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2016

🚗 Transport

💰 $150M Series C on 2021-03

Insurance • Transport

Zego is a company that provides flexible motor insurance solutions for various types of drivers and riders, including private hire taxi drivers, delivery drivers, and courier users. Zego's insurance products cover vehicles such as cars, scooters, motorbikes, and vans, and are designed to accommodate both personal and business use. Using technology such as the Sense telematics app, Zego offers personalized and potentially cheaper insurance premiums for safe drivers. The company collaborates with major delivery and ride-sharing platforms like Uber, Deliveroo, Just Eat, and Amazon Flex to offer tailored insurance options for their drivers. Zego emphasizes customer satisfaction, providing easy-to-use services via their app, and is a trusted provider for thousands of UK and European drivers.

📋 Description

• Design and build end-to-end ML systems from feature engineering through to model training, deployment, and monitoring • Develop and maintain the ML platform and tooling that enables the team (and the wider business) to ship models efficiently and reliably • Build and improve model lifecycle tooling: deployment, monitoring, alerting, and retraining for predictive models across multiple domains • Help extend the platform to new use cases and data domains as the team's scope grows • Collaborate closely with Data Scientists and Product teams to translate business problems into well-scoped ML solutions • Communicate complex technical concepts to both technical and non-technical stakeholders — clear thinking, clear storytelling

🎯 Requirements

• ML engineering experience: You've built, trained, and deployed production ML models, not just managed pipelines. You're comfortable across the full lifecycle, from experimentation to serving at scale. • Strong fundamentals: Solid grounding in machine learning techniques, you know when to reach for a GLM, when a gradient-boosted tree will do, and when something more complex is warranted. • Python: You've built production-grade Python applications and are fluent in the ML/data ecosystem (pandas, scikit-learn, and the usual suspects). • Platform & infrastructure: Hands-on experience with DevOps practices, Kubernetes, CI/CD, Docker, GitOps. You care about reliability and developer experience, not just model accuracy. • Cloud (AWS): You've worked in cloud environments, ideally AWS. • SQL: Strong SQL skills, particularly with cloud data warehouses (we use Snowflake). • Communication & collaboration: You translate ambiguous business needs into clear, actionable technical work. You've thrived in cross-functional teams with Data Scientists and Product Managers. • Technical leadership: You raise the bar for those around you through code reviews, design decisions, mentoring, and setting good engineering standards. • Experience in UK motor insurance or insurtech • Exposure to LLMs or LLMOps in a practical, production context • Experience with infrastructure-as-code (we use Terraform) • Experience with gRPC / protobuf

🏖️ Benefits

• Private medical insurance • Company share options • Generous holiday allowance • Wellbeing benefits