Amazon Applied Scientist II US Prime Marketing Tech 

United States, Washington, Seattle 

52442078

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

- 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