What you'll be doing

• Work within cross-functional teams alongside data scientists, software engineers, data engineers and product managers
• Design and deliver machine learning models at scale that create measurable impact for the business
• Own the end-to-end machine learning delivery lifecycle, including data exploration, feature engineering, model selection and tuning, evaluation, deployment and maintenance
• Shape technical direction for your area, making well-reasoned architectural and modelling decisions that stand up at scale
• Partner with and influence stakeholders across the business to propose innovative data products leveraging extensive datasets and latest algorithms
• Build tools, frameworks and libraries that accelerate the delivery of ML products and improve team workflows
• Provide technical mentorship and support the development of less experienced engineers, without formal people management responsibility
• Take an active role in the AI and ML community, fostering a culture of rigorous learning and experimentation

Requirements

• An advanced degree in Computer Science, Mathematics or related quantitative discipline, or equivalent experience
• Considerable experience productionising machine learning models, with strength in areas such as predictive modelling, classification, regression, optimisation or recommendation systems
• Strong proficiency in Python and open-source data libraries like Pandas, NumPy and Scikit-learn
• Solid grounding in statistical methodologies, data extraction, manipulation and feature engineering techniques
• Experience with Spark, agile delivery methods and CI/CD practices
• Familiarity with DevOps and MLOps tools and practices such as Docker, Terraform and MLFlow
• Confidence influencing and communicating with stakeholders across technical and non-technical teams

Nice to haves

• Exposure to cloud infrastructure, natural language processing or large language models (e.g. fine-tuning, retrieval-augmented generation, agents)
• Experience with graph technologies
• Experience in the transport sector or with geographic information systems (GIS)

Perks and benefits

• Private healthcare and dental insurance
• Generous work from abroad policy including 28-day Work from Abroad allowance
• 2-for-1 share purchase plans
• Electric Vehicle (EV) scheme to help reduce carbon emissions
• Extra festive time off
• Excellent family-friendly benefits
• Clear career paths, transparent pay bands and personal learning budgets
• Regular learning days to support career growth
• Hybrid working model requiring 60% office presence over 12 weeks