Applied Scientist II, Personalization, Grocery P13N

Amazon is hiring an Applied Scientist II, Personalization, Grocery P13N in Seattle, United States. It pays $143k-$193k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this applied scientist role is Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include LLMs, Transformers and Python.
Level classifies it as a senior role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

Develop cutting-edge machine learning and LLM-based models for real-time grocery personalization and recommendation systems.

LLMsTransformersPythonMachine Learning Frameworks

machine-learningapplied-sciencepersonalizationdeep-learningnatural-language-processing

Our goal is to be Earth's most customer-centric company, where customers can find and discover anything they might want to buy online. With our years of experience creating delight by fulfilling products from electronics to everyday essentials, our next challenge is offering customers fresh and delicious groceries—from seasonal fruits to your favorite cheeses. Our mission is to create the most intuitive and seamless grocery shopping experience by combining customer knowledge with LLM-based techniques that can deliver timely and relevant recommendations that make grocery shopping easy.

Are you passionate about applying cutting-edge machine learning to solve real-world customer problems? Do you want to build models that impact hundreds of millions of customers globally? This is a unique opportunity to innovate at the intersection of personalization science, large language models, and grocery shopping

As an Applied Scientist on the Grocery Personalization team, you will develop novel machine learning models and features that transform how customers discover and purchase groceries. You'll work on problems ranging from LLM-based techniques for understanding customer preferences and product relationships, transformer-based models for intent prediction, to large-scale real-time ranking systems that personalize the entire grocery shopping journey.

Key job responsibilities
- Innovate new features and models that have huge impact on the customer experience. Help customers find the right grocery products and content throughout their journey.

- Leverage the use of advanced LLM-based techniques to create customer grocery shopping experience at Amazon's scale - for all Amazon customers across all countries in realtime

- Be able to operate on a multidisciplinary team across science, product, design, and engineering to see through ideas from inception, prototype, to launch in the hands of all Amazon's customers

- Drive the science roadmap for the team

About the team
Amazon’s Personalization organization is a small, high-performing group that leverages Amazon’s expertise in machine learning, big data, and distributed systems to deliver the best shopping experiences for our customers. We work full stack, from foundational backend systems to future-forward user interfaces. Our team’s culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making. We run hundreds of experiments each year and our work has revolutionized e-commerce with features such as “Customers Who Bought Also Bought” and “Recommended for You”. We care deeply about our customers, as well as the well-being and growth of our team members. Amazon’s internal surveys regularly recognize us as one of the best engineering organizations to work for in the company, with visible high-impact work, low operational load, respectful work-life balance, and continual opportunity to learn and grow. This is a track record we are proud of and will continue to uphold. We are looking for creative and innovative leaders with a similar penchant for deeply-technical problem solving and the ability to lead, mentor, and deliver while upholding Amazon’s leadership principles.

Basic qualifications

- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Preferred qualifications

- Experience using Unix/Linux
- Experience in professional software development

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually

How we rate this

Applied Scientist II, Personalization, Grocery P13N at Amazon rates 90 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 Scientist II, Personalization, Grocery P13N is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $143k-$193k a year.
The role is based in US, WA, Seattle.
The job was posted on August 26, 2026.
Seniority: senior.
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

Machine learningApplied SciencePersonalizationDeep learningNatural Language ProcessingLLMsTransformersPython

Also common in applied scientist jobs at this level

Deep learning Generative AI NLP Reinforcement learning TensorFlow Spark

Pay

This job starts at: $143k
Typical applied scientist job: $169k

This posting starts 16% below the typical applied scientist job. See applied scientist jobs

Questions you could be asked

Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where applied science was part of your work. What did you do?
Tell me about a project where personalization was part of your work. What did you do?
Tell me about a project where deep 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?

Adapt your resume

List these exact terms on your resume: Machine learning, Applied Science, Personalization, Deep learning, and Natural Language Processing. 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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