Amazon Principal Applied Scientist Customer Engagement Technology 

United States, California, Cupertino 

121525225

Key job responsibilities
- Provide technical leadership, driving innovation and strategic direction for large-scale AI initiatives.
- Architect and develop ground-breaking ML modeling and engineering techniques, pushing boundaries of AI research and applications.
- Foster a culture of technical excellence, mentoring senior scientists and engineers.A day in the life
A typical day for a Principal Applied Scientist in the Customer Service Data and AI team involves a combination of gaining business know-how and hands-on problem-solving in NLP and GenAI. You'll tackle complex data initiatives, ensuring alignment with customer needs and business objectives, and translating business requirements into practical AI-driven solutions. Collaborating with cross-functional teams, you'll design and enhance AI models, focusing on efficiency, precision, and scalability. You'll mentor team members, fostering skill growth and encouraging innovative solutions. Your day involves monitoring data quality, evaluating model performance, and generating actionable insights from vast amounts of information. By the end of the day, you will have resolved complex technical issues, advanced important AI projects, and conceived new ideas to improve how Amazon utilizes data to transform the customer experience.Benefits Summary:1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan

- 7+ years of of building models for business application experience.
- Master's degree in computer science, machine learning, engineering, or related fields.

- Advanced degree (PhD) in Computer Science, Machine Learning, Engineering, or a related quantitative field.
- Hands-on experience developing and deploying GenAI applications, such as language models, text classification.
- Experience programming in Java, C++, Python or related language
- Strong understanding of GenAI or NLP fundamentals.
- Proficiency in designing and implementing large-scale data pipelines, and cloud-based data infrastructure.
- Proven track record of tackling highly ambiguous, complex data challenges and delivering impactful solutions.