Overview In this role you drive AI-powered innovation for Amazon Customer Service, shaping data-driven strategies and scalable solutions with GenAI, ML and NLP. You will translate complex business needs into practical AI systems, collaborating with cross-functional teams to improve customer and agent experiences. Expect to tackle data challenges, monitor model performance, and deliver measurable impact at global scale. This position offers a chance to set new standards for customer experience through advanced analytics and research-driven delivery.
Compensation / Benefits- health insurance
- 401(k) matching
- paid time off
- parental leave
- RSUs
- sign-on payments
Responsibilities- Develop innovative AI solutions to complex problems (e.g., trusted AI-enabled customer service)
- Implement novel algorithms and modeling solutions in collaboration with scientists and engineers
- Analyze data to define metrics and identify actionable insights improving customer experience
- Communicate results to technical and non-technical audiences via reports, presentations, and publications
- Collaborate with product management and engineering to deploy and optimize models in production
- Design and enhance AI models focusing on efficiency, precision, and scalability
- Ensure data quality and monitor model performance on large data sets
- Translate business requirements into practical AI-driven solutions across teams
Key requirements- 3+ years of experience building models for business applications
- Master's degree (or PhD) in CS, CE, ML or related field with substantial practical experience
- Experience with patents or publications at top-tier venues
- Proficiency in Java, C++, Python or related languages
- Strong background in algorithms, data structures, parsing, numerical optimization, data mining, and distributed computing
- excellent written communication
- ability to convey complex results to non-technical stakeholders
- cross-functional collaboration
- GenAI, ML, NLP
- embeddings and language modeling
- automated reasoning and knowledge representation
