Machine Learning Scientist III (Personalization)

TL;DR

Machine Learning Scientist III (Personalization): Building and optimizing real-time personalization engines for a global travel platform with an accent on deep learning, neural recommender systems, and scalable model deployment. Focus on designing complex retrieval and ranking architectures, conducting large-scale experimentation, and ensuring production-grade reliability for ML-powered services.

Location: Must be based in or able to work from San Jose, CA (Hybrid)

Salary: $149,000–$208,500

Company

hirify.global is a global travel technology company powering travel experiences through a diverse portfolio of brands and centralized personalization solutions.

What you will do

• Develop and advance scalable machine learning solutions for personalization, ranking, and recommendation use cases.
• Design and evaluate experiments to improve model performance and customer experience across multiple domains.
• Partner with engineering, product, and analytics teams to influence technical direction and deliver production-ready ML capabilities.
• Contribute to system design, API development, and data modeling for robust, maintainable ML services.
• Operate and integrate AI/ML-enabled solutions, ensuring high quality and operational performance in production environments.

Requirements

• Bachelor’s degree in Computer Science, Machine Learning, Statistics, or related field.
• 5+ years of professional experience in machine learning, applied science, or software development.
• Proven track record of delivering production-grade ML solutions within a service-oriented architecture.
• Strong foundation in machine learning methods, statistical analysis, and feature engineering.
• Proficiency in software engineering practices, including low-level design, API design, and data modeling.
• Must be authorized to work in the United States (E-Verify participant).

Nice to have

• Advanced degree (Master’s or PhD) in a technical field.
• Experience with neural recommendation systems, transformer-based models, or semantic retrieval.
• Familiarity with foundation models, LLMs, and hybrid LLM-recommender workflows.
• Experience with MLOps, model serving, and large-scale experimentation frameworks.

Culture & Benefits

• Comprehensive benefits package including medical, dental, and vision insurance.
• Flexible work model with office-based collaboration.
• Generous time-off policies and parental leave.
• Travel perks, wellness reimbursement, and IATAN membership.
• Career development resources and a culture that celebrates diversity and inclusion.