Machine Learning Scientist II (Personalization)

TL;DR

Machine Learning Scientist II (Personalization): Developing a centralized, real-time personalization engine for ranking and recommendations across brands and channels with an accent on deep learning foundations and sequential learning. Focus on building neural recommendation systems, implementing transformers, and evaluating agent personalization to improve the traveler journey.

Location: Geneva, Switzerland

Company

Global travel company connecting travelers, partners, and advertisers through leading technology and a network of consumer brands.

What you will do

• Develop and refine ML models for prediction, ranking, and recommendation for hirify.global products.
• Design end-to-end ML workflows, including feature engineering, model training, and A/B experimentation.
• Collaborate with software engineers and product managers to integrate ML solutions into scalable production systems.
• Analyze large-scale datasets to identify opportunities for model improvements and communicate findings to stakeholders.
• Apply statistical principles to ensure model quality and responsible use of data.
• Integrate AI/ML-enabled solutions to improve product outcomes and user experience.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related field.
• Professional experience applying ML or statistical modeling to real-world production environments.
• Hands-on experience with Python and deep learning frameworks such as PyTorch, TensorFlow, Keras, or JAX.
• Ability to independently own well-scoped ML components and collaborate with cross-functional partners.
• Familiarity with AI-driven systems and safely integrating AI/ML concepts into real-world products.

Nice to have

• Advanced degree (Master’s or PhD) focusing on applied ML or deep learning.
• Experience with neural recommendation, ranking, retrieval, or two-tower models.
• Expertise in sequential models, transformers, or attention-based architectures.
• Evidence of scientific curiosity through academic publications, open-source contributions, or research projects.
• Exposure to large-scale ETLs, model serving, and production ML monitoring.
• Interest in agent personalization, learned memory, or LLM evaluation.

Culture & Benefits

• Supportive environment fostering growth through values like Ownership Mindset and Succeed Together.
• Meaningful work helping millions of travelers globally discover and book travel.
• Flexibility, corporate benefits, and support for career growth.
• Inclusive and accessible recruiting experience.