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Applied Scientist, Perfect Order Experience (POE)

Amazon is hiring an Applied Scientist, Perfect Order Experience (POE) 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

  • Level rates this applied scientist role Builds AI ●●●●: the job is building AI systems.
  • The posting mentions Python, Java and C Plus Plus among its tools and skills.
  • Level classes it as a senior role.
  • Amazon has 20,000+ other open roles on Level.

AI in this role

Develop domain-specific foundation models and generative AI solutions for product risk and seller support.

PythonJavaC Plus Plus
machine-learningdeep-learninggenerative-aifoundation-modelsnlp
We’re pioneering frontier science solutions to detect and treat product quality issues and enhance post-order experience in Amazon. Our goal is to enhance support for our diverse seller community and foster improved outcomes for both sellers and consumers for broader Amazon ecosystem. We are looking for passionate innovators who are excited about technology, driven by customer experience, and eager to make a lasting impact on the industry.

In this role, you'll collaborate with top-tier scientists, engineers, and technical program managers (TPMs) to drive innovation in GenAI foundation models, adapt Large language model to our domain, develop efficient tabular foundation model, innovate on behavior foundation model. You will lead the effort to leverage Amazon's large-scale computing resources to accelerate advances in GenAI and frontier ML solutions. If you’re enthusiastic about joining a dynamic and motivated team, this is your chance to be part of an exciting journey. Apply now and help us shape the future of seller support at Amazon!

Key job responsibilities
1. Develop domain-specific foundation models.
2. Apply the domain-specific foundation model to product risk detection, seller interactions capturing, future seller behaviors prediction, and seller responses simulation across varied conditions.
3. Work with business and engineers to develop and deploy the solutions.

Basic qualifications

- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of science, technology, engineering or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience applying theoretical models in an applied environment

Preferred qualifications

- PhD
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning

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, Perfect Order Experience (POE) 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.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ 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.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Machine learningDeep learningGenerative AIFoundation ModelsNLPPythonJavaC Plus Plus

Also common in applied scientist jobs at this level

Pay

This job starts at
$143k
Typical applied scientist job
$167k

This posting starts 15% below the typical applied scientist job. See applied scientist jobs

Questions you could be asked

  1. Tell me about a project where machine learning was part of your work. What did you do?
  2. Tell me about a project where deep learning was part of your work. What did you do?
  3. Tell me about a project where generative ai was part of your work. What did you do?
  4. Tell me about a project where foundation models was part of your work. What did you do?
  5. What NLP problem have you worked on, and how did you measure whether it actually worked?

Adapt your resume

  • List these exact terms on your resume: Machine learning, Deep learning, Generative AI, Foundation Models, 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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