Thinking Machines LabRemote · San Francisco$350k-$475k5h ago
AmazonPosted 2mo ago
Applied Scientist, SP Support Science at Amazon scores 93 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
We are seeking a world-class Applied Scientist to help define and build the next generation of our LLM and ML systems. You will partner with applied scientists and engineers to design and deploy production-grade NLP pipelines, multi-modal AI frameworks, and scalable classification systems at Amazon's scale, owning your problem space end-to-end, from formulating a scientific approach to shipping a system that 50+ business teams rely on to make better decisions for millions of Selling Partners.
Key job responsibilities
- Use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of the tools that empower Amazon's Selling Partners to succeed.
- Design, develop and deploy highly innovative models to interact with Sellers and delight them with solutions.
- Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features.
- Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model validation and model implementation.
- Research and implement novel machine learning and statistical approaches.
- Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment.
About the team
Amazon's Selling Partner Support Science team builds the measurement and AI systems that power how Amazon understands, diagnoses, and eliminates the root causes of support contacts. Our vision is a continuous, science-driven pipeline where LLM-powered classification, causal impact measurement, and multi-modal friction detection work together to identify why Selling Partners experience frictions and quantify which interventions resolve them. Our systems process tens of millions of cases, evaluate hundreds of initiatives annually, and directly inform investment decisions across the Selling Partner Services organization.
Basic qualifications
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 3+ years of building machine learning models or developing algorithms for business application 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 in patents or publications at top-tier peer-reviewed conferences or journals
- Experience in investigating, designing, prototyping, and delivering new and innovative system solutions
- Experience developing, deploying and managing AI products at scale
- Demonstrated experience leveraging generative AI tools to enhance workflow efficiency and productivity, with the ability to craft effective prompts and critically evaluate AI-generated outputs in a professional setting
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
- 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: 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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