PerplexityBerlin
AmazonPosted 4mo ago
Applied Scientist, AWS Insights & Optimization
Applied Scientist, AWS Insights & Optimization at Amazon scores 88 out of 100 on AI centrality, which makes it a Level 4 role on this board.
AI in this role
As a successful Applied Scientist in AWS Insights & Optimization, you will own models end-to-end — from problem formulation through experimentation to production deployment. Your work may span cost anomaly detection (decomposition, detection, and root cause attribution), time-series forecasting with a focus on accuracy and consistency, rightsizing engines for EC2, EBS, Lambda, ECS, RDS, and Aurora, LLM evaluation science for AI-powered agent experiences, or agent memory architectures that enable persistent, adaptive behavior across sessions. You will work closely with applied scientists, software engineers, and product teams to enhance existing models and build new ones that solve challenging customer problems. You will drive implementation of proposed models, establish testing strategies to validate them before and after production, and define evaluation metrics that determine whether capabilities meet the quality bar. We value accuracy over speed, measurability over intuition, and simplicity over complexity — the simplest model that meets the bar wins. You are an analytical problem solver who enjoys diving into data, are excited about investigating and developing algorithms, and can influence technical teams and business stakeholders to solve real-world customer problems.
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 in patents or publications at top-tier peer-reviewed conferences or journals
- 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
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide that one model's output is better than another's for a given task?
- 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: AI Evaluation. 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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