Applied Scientist III, AGI Responsible AI (RAI)

AI in this role

Applied Scientist leading the design of responsible AI evaluation methods and benchmarks for large language models.

tensorflowscikit-learnpythonjavacpytorchspark

ai-evaluationai-safetymachine-learninglarge-language-modelsresponsible-aievaluation-frameworksdeep-learning

Amazon's Artificial General Intelligence (AGI) organization is seeking an Applied Scientist III to advance the science of Responsible AI evaluation for large language models and generative AI. In this role, you will lead the design and development of rigorous evaluation methods, benchmarks, and metrics that measure the safety, fairness, robustness, and trustworthiness of frontier models. You will work with large-scale datasets, modern deep learning frameworks, and world-class scientists and engineers to turn research into evaluation systems that shape model launch decisions at Amazon scale.

Key job responsibilities
- Lead the design and implementation of evaluation frameworks, benchmarks, and metrics for responsible AI, including safety, fairness, robustness, and harmful content.
- Build scalable automated evaluation pipelines for large language models, including model-based and human-in-the-loop evaluation.
- Partner with pretraining, post-training, and product teams to translate evaluation results into model improvements and launch decisions.
- Conduct rigorous experimentation and statistical analysis, and publish research at top venues.
- Mentor junior scientists and help raise the scientific bar of the team.
- Champion responsible AI practices across the model development lifecycle.

About the team
The AGI Responsible AI (RAI) team builds the science and systems that make Amazon's large language models safe, fair, and trustworthy. We work on problems spanning safety evaluation, content moderation, watermarking, bias mitigation, and alignment. Our team values scientific rigor, customer obsession, and rapid iteration, and we collaborate closely with pretraining, post-training, and product teams across AGI.

Basic qualifications

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

Preferred qualifications

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.

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, Sunnyvale - 192,200.00 - 260,000.00 USD annually
USA, MA, Boston - 167,100.00 - 226,100.00 USD annually

How we rate this

Applied Scientist III, AGI Responsible AI (RAI) 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. Open the description and count.

Key facts

Applied Scientist III, AGI Responsible AI (RAI) is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $192k-$260k a year.
The role is based in US, CA, Sunnyvale.
The job was posted on October 7, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

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

AI EvaluationAI SafetyMachine learningLarge Language ModelsResponsible AIEvaluation FrameworksDeep learningTensorFlow

Questions you could be asked

How do you decide that one model's output is better than another's for a given task?
How do you think about the risk of an AI system in this kind of role failing silently?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where large language models was part of your work. What did you do?
Tell me about a project where responsible ai was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI Evaluation, AI Safety, Machine learning, Large Language Models, and Responsible AI. 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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