The Role
At Canopius, our Data team is responsible for ensuring that business teams can effectively harness data insights to drive strategic decision making. Our data strategy is centred around an enterprise Lakehouse platform on Databricks, avoiding fragmented, ungoverned silos on legacy technologies that hamper creativity and scalability.
The Senior Machine Learning Engineer owns the end-to-end design, delivery and operation of production machine learning (ML) models, working within cross-functional squads to deliver cohesive solutions. The ideal candidate will be an experienced ML engineer looking for a new challenge who is enthusiastic about using technology to accelerate change within our industry. You should have the ability to understand business problems and deliver efficient and reliable solutions tailored to our unique challenges, while keeping to a high degree of technical excellence and good data practices. You should be comfortable collaborating and working as part of a dynamic, multi-disciplinary team.
Responsibilities
- Lead the design, development, testing, deployment, and ongoing monitoring of machine learning solutions on Databricks, ensuring continuous optimisation and retraining as needed.
- Define and embed best practice standards and processes for MLOps in Databricks, ensuring appropriate version and access control, model governance and monitoring strategies are established.
- Develop and maintain automated validation tests for models, encompassing unit, integration, regression, and bias assessments.
- Assess stakeholder requirements and determine suitable machine learning approaches, ensuring that all ethical and privacy considerations are identified and appropriately managed.
- Establish clear criteria for evaluating the reliability of model outputs, as well as key performance indicators to monitor production systems.
- Create and update documentation for models, covering their assumptions, methods, metrics, potential failure modes, and sensitivity analysis.
- Ensure complete traceability of datasets and results, and manage machine learning model audit requests, including gathering supporting evidence.
- Work collaboratively within cross-functional teams to deliver aligned solutions within established deadlines.
- Lead the identification of underlying causes of production ML model issues.
- Educate the wider teams on the techniques and approaches used to help build common understanding.
- Keep up to date with new features and trends in the evolving ML landscape, proposing how we could leverage new capabilities to enhance existing solutions.
Skills and Experience
- Bachelor’s degree or higher in STEM subject (or equivalent); able to demonstrate confident understanding of statistical methods.
- Strong background in machine learning, data science and/or data engineering.
- Proficient in writing production‑grade, scalable SQL, Python and PySpark code.
- Results‑oriented, with a proven track record of delivering ML models to production.
- Strong experience of establishing and embedding MLOps processes on Databricks.
- Experienced in constructing pipelines to prepare structured and unstructured datasets for ML models.
- Excellent analytical and problem‑solving skills, with a keen eye for detail.
- Experience of working autonomously to own task list as well as collaboratively within an Agile environment.
- Able to adapt quickly to shifting priorities, communicating issues and blockers early.
- Demonstrated ability to communicate effectively with stakeholders across all levels and functions of the business, including translating complex technical concepts into clear, accessible language suitable for non‑technical audiences.
Competencies
- Stakeholder engagement: Translates complex business problems into robust machine learning solutions, working closely with stakeholders to define requirements, success measures, and ethical considerations. Communicates technical concepts clearly and confidently to non‑technical audiences.
- Collaboration and teamwork: Works effectively within cross‑functional, agile squads to deliver end‑to‑end ML solutions on time and to a high standard. Actively shares knowledge and supports team capability through coaching and education.
- Adapting to change: Responds quickly to shifting priorities and evolving requirements, proactively flagging risks and blockers. Maintains delivery momentum while balancing experimentation with production stability.
- Continuous Improvement: Defines, embeds, and evolves best‑practice MLOps standards, governance, and monitoring to improve reliability, traceability, and performance of production ML systems. Uses data, testing, and metrics to drive ongoing optimisation.
- Innovation: Keeps pace with advances in machine learning and data platforms, identifying opportunities to apply new techniques and Databricks capabilities to real business challenges. Champions scalable, modern approaches over legacy solutions.
- Resilience: Owns production ML models end‑to‑end, diagnosing and resolving complex issues with a methodical, evidence‑based approach. Maintains high quality and control under pressure, including audit and regulatory scrutiny.
- Future Focused: Builds ML solutions with long‑term scalability, governance, and enterprise data strategy in mind. Contributes to a sustainable Lakehouse ecosystem that enables future growth, creativity, and strategic decision‑making.
About Us
Our benefits: We offer all employees a comprehensive benefits package that focuses on their whole wellbeing. This includes hybrid working, a competitive base salary, non‑contributory pension, discretionary bonus, insurances including health (family) and dental cover, and many other benefits to enhance financial, physical, social and psychological health.
About Canopius: Canopius is a global specialty lines (re)insurer. We are one of the leading insurers in the Lloyd’s of London insurance market with offices in the UK, US, Singapore, Australia and Bermuda.
At Canopius we foster a distinctive, positive culture which enables us to bring our whole selves to work to flourish as people, and build a business which delivers profitable, sustainable results.
Based in incredible new offices in the heart of the City of London, Canopius operates a flexible, hybrid working model and is committed to providing an environment that challenges employees to be their best and where everyone's unique contributions are recognised, valued and respected.
We are fully committed to equal employment opportunities for all applicants and providing employees with a work environment free of discrimination and harassment. All employment decisions are made regardless of age, sex, gender identity, ethnicity, disability, sexual orientation, socio‑economic background, religion or beliefs, marital or caring status, or any other status protected by the laws or regulations in the locations where we operate. We encourage and welcome applicants from all diverse backgrounds.
We make reasonable adjustments throughout the recruitment process and during employment. Please let us know if you require any information in an alternate format or any other reasonable adjustments.
