1 week ago
Software Development Engineer, Alexa Personalization
US, WA, Bellevue
We are seeking talents to design and build the Personalized Ambient Context (PAC) Provider to intelligently provide relevant and summarized interaction, situational, and personal context to the LLM based Alexa prompt, to provide personalized experience for every customer interaction, cohere and engage further interactions with customers. The candidate is expected to be able to deal with large scale and low latency challenges, deliver in an environment with a high velocity and lots of ambiguities by working across multiple roles from both internal and external partner teams.
Key job responsibilities
The Software Development Engineer will:
- Collaborate with Data Scientists team and build Personalized Ambient Context service to interact with Search Model to predict relevant context signals from customer interaction, and interact with Summarization Model to summarize retrieved context values in natural language format.
- Work closely with Data Scientists to continuously improve Machine-Learning models performance to predict the relevant interaction, situational, and personal context in more accurate and intelligent way.
- Build horizontal experimentation framework that provides hooks to experiment different configurations and threshold across various components.
- Build context query executor and execute the query in optimal matter to retrieve the context data with low latency.
- Work with other team members to investigate design approaches, prototype new technologies and evaluate technical feasibility.
- Work in an Agile/Scrum environment to deliver high-quality software in a fast-paced environment.
About the team
Generalized ai Enhanced Natural and Intuitive Experiences (GENIE) mission is to "accelerate personalized and intuitive experiences that enhance customer satisfaction and benefit all Amazon businesses". Our goal is to provide conversational, visual and proactive mechanisms to delight customers, increase customer engagement, reduce defects, and enable natural interactions across Amazon touch points (e.g., Alexa, Stores, Mobile). To achieve our mission, we build automated, scalable, self-serve AI systems that use customer, device and ambient signals to offer personalized suggestions, comprehend customer inputs, learn from customer interactions, reduce defects, and propose appropriate actions to serve millions of Amazon customers across the globe.
Key job responsibilities
The Software Development Engineer will:
- Collaborate with Data Scientists team and build Personalized Ambient Context service to interact with Search Model to predict relevant context signals from customer interaction, and interact with Summarization Model to summarize retrieved context values in natural language format.
- Work closely with Data Scientists to continuously improve Machine-Learning models performance to predict the relevant interaction, situational, and personal context in more accurate and intelligent way.
- Build horizontal experimentation framework that provides hooks to experiment different configurations and threshold across various components.
- Build context query executor and execute the query in optimal matter to retrieve the context data with low latency.
- Work with other team members to investigate design approaches, prototype new technologies and evaluate technical feasibility.
- Work in an Agile/Scrum environment to deliver high-quality software in a fast-paced environment.
About the team
Generalized ai Enhanced Natural and Intuitive Experiences (GENIE) mission is to "accelerate personalized and intuitive experiences that enhance customer satisfaction and benefit all Amazon businesses". Our goal is to provide conversational, visual and proactive mechanisms to delight customers, increase customer engagement, reduce defects, and enable natural interactions across Amazon touch points (e.g., Alexa, Stores, Mobile). To achieve our mission, we build automated, scalable, self-serve AI systems that use customer, device and ambient signals to offer personalized suggestions, comprehend customer inputs, learn from customer interactions, reduce defects, and propose appropriate actions to serve millions of Amazon customers across the globe.