Amazon Stores is looking for exceptional Applied Scientists to join our efforts in developing generative AI solutions in marketing. In this role, you will be part of a team that designs, implements, and evaluates state-of-the-art agentic AI solutions to enhance customer experiences through intelligent, personalized interactions.
Key job responsibilities
Research, develop, and deploy novel approaches using large language models (LLMs) and multi-agent AI systems
Design and implement scalable solutions for personalized recommendations and customer insights
Create innovative evaluation frameworks for complex AI systems
Collaborate with cross-functional teams to integrate AI solutions into production environments
Conduct rigorous experimentation and data analysis to improve model performance
PhD in Computer Science, Machine Learning, AI, or related field; OR Master's degree with 2+ years of relevant industry experience
Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, etc.)
Experience building and deploying machine learning models in production environments
Proficiency in natural language processing techniques and applications
Strong publication record or demonstrated practical experience in machine learning
Experience working with large language models (LLMs) and prompt engineering
Knowledge of multi-agent systems and their applications
Background in recommendation systems or personalization technologies
Experience with uncertainty quantification in AI systems
Ability to design and implement automated testing frameworks for ML systems
Previous experience in AI labs or AI-focused startups
Strong communication skills and ability to translate complex technical concepts to diverse audiences
Experience with model evaluation and validation methodologies
Track record of innovation in applied machine learning
BASIC QUALIFICATIONS - PhD in Computer Science, Machine Learning, AI, or related field; OR Master's degree with 2+ years of relevant industry experience
- Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, etc.)
- Experience building and deploying machine learning models in production environments
- Proficiency in natural language processing techniques and applications
- Strong publication record or demonstrated practical experience in machine learning
PREFERRED QUALIFICATIONS - Experience working with large language models (LLMs) and prompt engineering
- Knowledge of multi-agent systems and their applications
- Background in recommendation systems or personalization technologies
- Experience with uncertainty quantification in AI systems
- Ability to design and implement automated testing frameworks for ML systems
- Previous experience in AI labs or AI-focused startups
- Strong communication skills and ability to translate complex technical concepts to diverse audiences
- Experience with model evaluation and validation methodologies
- Track record of innovation in applied machine learning
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 for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit . This position will remain posted until filled. Applicants should apply via our internal or external career site.
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