Machine Learning Engineer

Company Description

Launched in 1998, this pioneering British-born brand has specialised in creating unforgettable experiences - from city breaks, hotels and holidays to theatre and spa days. is among the worldwide leaders in the field, helping hundreds of thousands of customers every year find, and do, "whatever makes them pink". is part of lm group, a publicly-traded multinational Group, among the worldwide leaders in the online travel industry. Each month, our websites and mobile apps (available in 17 languages and 40 countries) reach 43 million unique users that search for and book their travel and leisure experiences.

More than 1,200 people enjoy working with us and contribute to providing our audience with a comprehensive and inspiring offering of travel-related products and services

Job Description

We are looking for a highly qualified and motivated Machine Learning Engineer to work on large-scale machine learning pipelines and scale it even further. The selected candidate will be part of a cross-functional team composed of machine learning/data scientists, data analysts, and machine learning/data engineers. This position is based in our office in Chiasso (Switzerland) or eventually full-remote.

Key Responsibilities 

  • Contribute to designing, building, and shipping highly scalable machine learning pipelines
  • Optimize deep learning models to improve serving-time performance and scalability
  • Ensure quality by applying unit, acceptance, and end-to-end tests
  • Prototype and productionize new solutions at scale
  • Collaborate closely with machine learning scientists, software engineers, and data analysts



  • Experience in designing, implementing, and deploying production machine learning systems
  • Strong coding skills in Python and Java
  • Experience with Spark
  • Strong SQL knowledge
  • Familiar with engineering principles around testing, code review, and deployment
  • Good understanding of deep learning models, pragmatic mindset, and ability to evolve ideas into practical implementations
  • Experience in implementing and maintaining scalable data pipelines
  • Experience with Docker
  • Experience with distributed version control systems


  • Experience with cloud platforms like GCP and/or AWS
  • Experience with  publisher/subscriber system
  • Experience with  Kubernetes
  • Experience with Keras
  • Experience with TensorFlow
  • Experience with NoSQL databases
  • Curious with a constant desire to learn and collaborate

Additional Information

  • We ask you to attach your CV in English