Applied Science Manager (Personalization)

TL;DR

Applied Science Manager (Personalization): Leading a team to build hirify.global’s next-generation customer memory and personalization systems with an accent on LLM reasoning and knowledge representation. Focus on transforming unstructured signals into high-quality customer preferences and deploying scalable ML solutions to improve the shopping experience.

Location: ISR, Haifa / Tel Aviv

Company

hirify.global is a global technology leader leveraging large-scale machine learning and generative AI to deliver highly relevant customer experiences.

What you will do

• Lead a team of scientists developing LLM-powered memory and personalization systems.
• Define the scientific direction for how customer knowledge is extracted, validated, and applied in production.
• Own the end-to-end delivery of ML solutions, from problem formulation and modeling to online experimentation and large-scale deployment.
• Drive initiatives in fact extraction, memory quality, temporal reasoning, and grounded personalization.
• Hire and develop scientific talent while fostering a culture of ownership and rigor.
• Partner with engineering and product teams to translate research into measurable customer impact.

Requirements

• PhD, or Master’s degree with 6+ years of applied research experience in machine learning or a related field.
• 3+ years of experience managing Applied Scientists or ML Engineers.
• Proven track record of deploying end-to-end ML solutions including A/B testing at scale.
• Hands-on experience applying modern machine learning techniques, including Deep Learning and Large Language Models (LLMs).
• Experience leading cross-team initiatives and defining roadmaps in ambiguous environments.
• Strong communication skills with the ability to influence senior leadership.

Nice to have

• Experience with LLM training, fine-tuning, adaptation, or large-scale inference.
• Expertise in Recommendation Systems, Information Retrieval, or NLP.
• Experience with sequential recommendation, user intent, or behavioral modeling.