Applied Scientist (GenAI/LLM), Sandstone

Amazon is hiring an Applied Scientist (GenAI/LLM), Sandstone 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 PyTorch, TensorFlow and scikit-learn among its tools and skills.
Level classes it as a mid-level role.
Amazon has 21,000+ other open roles on Level.
Posted in the last few days.

AI in this role

pytorchtensorflowscikit-learn

computer-visionnlp

Do you want to join an innovative team of scientists and engineers who use terabytes of data and create state-of-the-art Generative AI algorithms to push the boundaries of AI creativity? We are building foundational behavioral models for Amazon Stores using Generative AI, LLMs and Large Model training techniques that fuses general world knowledge, customer shopping behavior and Amazon e-commerce domain knowledge. We are looking for scientists who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry using intelligent and transformative AI applications. Working closely with cross-functional teams, you will be an essential part of every stage of AI development, from ideation and design to rigorous testing and successful deployment, ensuring our AI projects drive innovation and provide value for our customers. If you’re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!

Key job responsibilities
In this role you will leverage your background and expertise to lead developing foundational behavioral model for Amazon Stores using Generative AI, LLM and Large Model training techniques. On a day-to-day basis, you will:
- Research and implement new algorithms and architectures for generative AI applications.
- Optimize model performance and scalability for inference and deployment.
- Collaborate with other talented applied scientists and engineers to gather and preprocess large datasets and develop an improved training infrastructure that accelerates innovation.
- Experiment with SOTA methods to improve generative AI model quality.
- Provide technical expertise and guidance to support the integration of generative AI solutions into various products and services.

Basic qualifications

- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 2+ years of building models 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
- Experience in patents or publications at top-tier peer-reviewed conferences or journals

Preferred qualifications

- Strong understanding of machine learning, deep learning, and generative AI principles and algorithms.
- Proficiency with modeling and large-scale data processing tools such as Pytorch, scikit-learn, Spark MLLib, PySpark, MxNet, Tensorflow, numpy, scipy etc.
- Ability to work with large datasets and knowledge of data preprocessing techniques such as Hadoop, Spark etc..
- Familiarity with natural language processing (NLP) and computer vision for generative AI applications.
- Strong problem-solving and critical thinking skills and excellent communication and teamwork abilities to collaborate with cross-functional teams.
- Ability to stay updated with the latest advancements in generative AI and adapt to new techniques and methodologies.

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

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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, CA, San Diego - 142,800.00 - 193,200.00 USD annually
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually

How we rate this

Applied Scientist (GenAI/LLM), Sandstone at Amazon rates 94 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 (GenAI/LLM), Sandstone 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 October 26, 2026.
Seniority: mid.
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

Computer visionNLPPyTorchTensorFlowscikit-learn

Also common in applied scientist jobs at this level

Reinforcement learning AWS Fine-tuning AI agents RAG SQL

Pay

This job starts at: $143k
Typical applied scientist job: $172k

This posting starts 17% below the typical applied scientist job. See applied scientist jobs

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?
What are the limits of PyTorch that you've run into, and how did you work around them?
What's a project where you used TensorFlow hands-on?
Walk me through how you've used scikit-learn in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Computer vision, NLP, PyTorch, TensorFlow, and scikit-learn. 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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