LambdaRemote · Bellevue Office$399k-$531k
AmazonPosted 3mo ago
L4
Applied Science Manager, Personalization
Applied Science Manager, Personalization at Amazon scores 98 out of 100 on AI centrality, which makes it a Level 4 role on this board.
IL, Haifamidfull-time
AI in this role
fine-tuningnlp
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.
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Skills and AI tools this role asks for
Fine TuningNlp
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?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: Fine Tuning and Nlp. 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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