AI & Emerging technologies

Machine Learning Engineering Manager

Trainline

London · Greater London · United Kingdom

Overview

In this role you will lead a cross-functional ML team to deliver scalable AI-powered solutions that enhance Trainline’s platform and customer experience. You will own the end-to-end ML delivery lifecycle, from data exploration to deployment, while partnering with product and engineering to create data-driven products. You’ll shape the ML and AI strategy within a fast-growing, sustainability-driven company and mentor a diverse group of engineers, scientists and managers.

Pay / Benefits
  • private healthcare
  • dental insurance
  • work from abroad policy
  • 2-for-1 share purchase plans
  • EV scheme
  • family-friendly benefits
Responsibilities
  • Lead a high-performing ML Engineering team alongside Software Engineers, Data Scientists, Data Engineers and Product Managers
  • Deliver high-quality machine learning models and AI systems at scale with measurable business impact
  • Own end-to-end ML lifecycle: data exploration, feature engineering, model selection, offline/online evaluation, deployment and maintenance
  • Collaborate with stakeholders to propose innovative data products leveraging Trainline datasets and algorithms
  • Foster a culture of learning, experimentation and knowledge sharing within AI/ML communities
Key requirements
  • Advanced degree in Computer Science, Mathematics or a similar quantitative discipline
  • Leadership experience either through management or mentorship
  • Proficiency in Python with libraries (Pandas, NumPy, Scikit-learn)
  • Experience productionising machine learning models
  • Expertise in at least one area: predictive modelling, classification, regression, optimisation or recommendation systems
  • Experience with Spark
  • Knowledge of DevOps tools (Docker, Terraform) and MLOps practices (MLflow)
  • Experience with agile delivery, CI/CD processes and tools
  • Broad understanding of data extraction, manipulation and feature engineering techniques
  • Familiarity with statistical methodologies
  • Strong communication skills
  • leadership
  • clear communication
  • collaboration
  • Python and ML/DS libraries (scikit-learn, numpy, LightGBM, Pandas)
  • PySpark
  • AWS cloud infra (EMR, ECS, Athena)

Reference: WJ-747_31165291

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