Senior Machine Learning Engineer (AI)

Location: London, UK; hybrid work with a minimum of 60% office attendance over a 12-week period. A 28-day work-from-abroad policy is available.

Company

hirify.global is a FTSE 250 travel technology company that helps travellers search and book rail and coach journeys through consumer and B2B channels.

What you will do

• Design, deploy, evaluate, and maintain machine learning models at scale.
• Own the full ML delivery lifecycle, from data exploration and feature engineering to production maintenance.
• Make architectural and modelling decisions that support reliable, scalable systems.
• Work with data scientists, software engineers, data engineers, and product managers to deliver measurable business impact.
• Build tools, frameworks, and libraries that accelerate ML product development.
• Mentor less experienced engineers and contribute to the AI and ML community.

Requirements

• Advanced degree in Computer Science, Mathematics, or a related quantitative discipline, or equivalent experience.
• Significant experience productionising machine learning models in areas such as predictive modelling, classification, regression, optimisation, or recommendation systems.
• Strong Python skills and experience with Pandas, NumPy, and Scikit-learn.
• Knowledge of statistics, data extraction, data manipulation, and feature engineering.
• Experience with Spark, agile delivery, and CI/CD practices.
• Familiarity with DevOps and MLOps tools including Docker, Terraform, and MLflow, plus strong stakeholder communication skills.

Nice to have

• Experience with cloud infrastructure, NLP, large language models, fine-tuning, RAG, AI agents, graph technologies, transport, or GIS.

Culture & Benefits

• Hybrid work with a minimum of 60% office attendance and a 28-day work-from-abroad policy.
• Private healthcare and dental insurance, family-friendly benefits, and extra festive time off.
• Two-for-one share purchase plan and an electric vehicle scheme.
• Clear career paths, transparent pay bands, personal learning budgets, and regular learning days.
• Inclusive culture focused on ownership, collaboration, innovation, and sustainable travel.