Machine Learning Scientist III (Personalization)

TL;DR

Machine Learning Scientist III (Personalization): Building hirify.global's centralized, real-time personalization engine to power ranking and recommendations with an accent on deep learning and neural recommender systems. Focus on developing scalable production ML systems, optimizing retrieval and ranking, and integrating LLMs for adaptive traveler experiences.

Location: Switzerland - Geneva (Flexible work model)

Company

hirify.global brands power global travel for everyone, everywhere, designing cutting-edge tech to make travel smoother and more memorable.

What you will do

• Develop and advance ML solutions for personalization, translating business problems into production-ready models.
• Design experiments and evaluate performance to improve relevance, ranking, and recommendations.
• Partner with engineering, product, and analytics teams to define technical direction and ML capabilities.
• Contribute to feature design, data preparation, and the operationalization of ML solutions in production.
• Apply technical judgment to system and API design for maintainable ML-powered services.
• Integrate AI/ML-enabled solutions and workflows to improve real-world product outcomes.

Requirements

• Bachelor’s degree in Computer Science, ML, Statistics, Mathematics, or equivalent professional experience.
• 5+ years of relevant experience in machine learning, applied science, or software development, including delivering production-grade ML solutions.
• Demonstrated ownership of ML solutions with accountability for model quality and operational performance.
• Strong foundation in statistical analysis, experimentation, and feature engineering with large-scale datasets.
• Proficiency in software engineering practices, including coding, API design, and data modeling.

Nice to have

• Advanced degree in ML, Computer Science, Statistics, or Mathematics.
• Experience scaling recommendation, ranking, or retrieval models in complex consumer-facing environments.
• Knowledge of neural recommendation systems, transformer-based recommenders, or representation learning.
• Experience with LLMs, embedding models, and retrieval-augmented personalization workflows.
• Familiarity with MLOps, model serving, and feature/data pipelines.

Culture & Benefits

• Flexible work model with access to modern office spaces.
• Full benefits package including exciting travel perks.
• Generous time-off and parental leave.
• Career development resources and an inclusive, open culture.