Applied Science Manager, Personalization

Amazon is hiring an Applied Science Manager, Personalization in Haifa, Israel. Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this role Builds AI ●●●●: the job is building AI systems.
The posting mentions Python, PyTorch and LLMs among its tools and skills.
Level classes it as a lead role.
Amazon has 20,000+ other open roles on Level.

AI in this role

Lead a team of applied scientists building next-generation e-commerce personalization systems powered by Large Language Models.

PythonPyTorchLLMs

fine-tuningnlpmachine-learningnatural-language-processingrecommendation-systemsinformation-retrievalteam-management

Are you a scientist interested in pushing the state of the art in Information Retrieval, Large Language Models and Recommendation Systems? Are you interested in innovating on behalf of millions of customers, helping them accomplish their every day goals? Do you wish you had access to large datasets and tremendous computational resources? Do you want to join a team of capable scientist and engineers, building the future of e-commerce? Answer yes to any of these questions, and you will be a great fit for our team at Amazon.

Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, generative AI, large-scale data systems, and user experience design to deliver the best shopping experiences for our customers. Our team is building next-generation personalization systems powered by Large Language Models. We are tackling novel research challenges to help customers discover products they'll love - at Amazon scale and latency requirements. We are a team uniquely placed within Amazon, to have a direct window of opportunity to influence how customers will think about their shopping journey in the future.

As an Applied Science Manager, you will lead a team of scientists working at the frontier of LLM-based personalization. You will set the technical vision, drive the research agenda, and ensure your team delivers production-ready solutions. You will hire, mentor, and develop world-class scientists while fostering a culture of innovation and scientific rigor. You will partner closely with engineering and product teams to translate ambitious research into customer-facing impact, and represent your team's work to senior leadership.

Please visit https://www.amazon.science for more information.

Basic qualifications

- PhD or equivalent research experience, or Master's degree
- 3+ years of scientists or machine learning engineers management experience
- 3+ years of experience leading teams that build and deploy ML models for business applications
- Experience leading applied research in one or more of: Recommendation Systems, Information Retrieval, NLP, or Large Language Models
- Demonstrated ability to think strategically, communicate effectively (written and verbal) with senior leadership, and drive cross-team collaboration

Preferred qualifications

- Experience with LLM training, fine-tuning, or adaptation (e.g., tokenizer modification, domain adaptation)
- Experience with sequential recommendation, user intent/mission modeling, or behavioral modeling

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

How we rate this

Applied Science Manager, Personalization at Amazon rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Applied Science Manager, Personalization is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in IL, Haifa.
The job was posted on June 8, 2026.
Seniority: lead.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Fine-tuningNLPMachine learningNatural Language ProcessingRecommendation SystemsInformation RetrievalTeam ManagementPython

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
What NLP problem have you worked on, and how did you measure whether it actually worked?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where natural language processing was part of your work. What did you do?
Tell me about a project where recommendation systems was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Fine-tuning, NLP, Machine learning, Natural Language Processing, and Recommendation Systems. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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