Senior ML Engineer

• Design, build, and own end-to-end matchmaking, recommendation, ranking, and personalisation systems
• Develop a real-time adaptive matchmaking engine that learns continuously from user interactions and behavioural signals
• Build user embedding systems, similarity models, and graph-based match scoring frameworks
• Architect and implement cold-start solutions to deliver quality recommendations for new users with sparse data
• Deploy models to production with fast iteration loops, model registries, and observability tooling
• Define and track offline and online evaluation frameworks, A/B tests, and metric alignment across the recommendation stack
• Partner with Data, Product, and Backend teams to translate business goals into scalable ML solutions

Must Have Criteria

• 2–5 years of hands-on experience building personalisation, recommendation, ranking, or search systems at scale
• Prior experience at a B2C product company or startup — social, e-commerce, fashion, gaming, dating, or video platforms
• Working knowledge of collaborative filtering, two-tower deep retrieval models, learning-to-rank, and embedding-based ANN search
• End-to-end ML pipeline ownership — both training models and deploying them to production
  • Familiarity with offline and online evaluation methodologies, A/B testing, and metric alignment