Alexa Daily Essentials is hiring an Applied Scientist to research and implement large language model innovations to enhance Alexa's language understanding, knowledge representation, reasoning and generation capabilities.
The Alexa Daily Essentials team delivers experiences critical to how customers interact with Alexa as part of daily life. We drive over 40 billion+ actions annually across 60 million+ monthly customers, who engage with our products across experiences connected to Timers, Alarms, Calendars, Food, and News. Our experiences include critical time saving techniques, ad-supported news audio and video, and in-depth kitchen guidance aimed at serving the needs of the family from sunset to sundown. Our upcoming launches are at the forefront of innovation, delivering step-function improvements in experiences that stretch across the customer journey, and new AI technologies that will enable customers to send Alexa information for future recall and conversation. We collaborate closely with partners such as Amazon.com, Whole Foods, Spotify, CNN, Fox, NPR, BBC, Discovery, and Food Network to deliver our vision. If you are passionate about redefining the personal assistant experience and leveraging innovative technology to improve daily life, we’d love to hear from you. This is an opportunity to make a tangible impact at the heart of the Alexa ecosystem.
As an applied scientist, you will advance state of the art techniques in ML and LLM, and work closely with product and engineering teams to build the next generation of the Alexa smart assistant.
Key job responsibilities
- Rapidly prototype ML/LLM solutions, evaluate feasibility, and drive projects to production deployment
- Continuously monitor and improve model performance through retraining, parameter tuning, and architecture refinements
- Develop new training and inference techniques to improve model performance
- Work cross-functionally across engineering, product, and business teams to understand customer needs, scope science work, and drive science solutions from conception to customer delivery
- Research and develop LLM innovations, and lead paper publications.
- Code proficiently in Python (required) and Java (preferred); optimize systems for high performance at scale; contribute code directly into production services
- Innovate and develop science and engineering solutions that optimize team operations and increase team effectiveness.
- Clearly communicate complex technical concepts to non-technical stakeholders and leadership
The Alexa Daily Essentials team delivers experiences critical to how customers interact with Alexa as part of daily life. We drive over 40 billion+ actions annually across 60 million+ monthly customers, who engage with our products across experiences connected to Timers, Alarms, Calendars, Food, and News. Our experiences include critical time saving techniques, ad-supported news audio and video, and in-depth kitchen guidance aimed at serving the needs of the family from sunset to sundown. Our upcoming launches are at the forefront of innovation, delivering step-function improvements in experiences that stretch across the customer journey, and new AI technologies that will enable customers to send Alexa information for future recall and conversation. We collaborate closely with partners such as Amazon.com, Whole Foods, Spotify, CNN, Fox, NPR, BBC, Discovery, and Food Network to deliver our vision. If you are passionate about redefining the personal assistant experience and leveraging innovative technology to improve daily life, we’d love to hear from you. This is an opportunity to make a tangible impact at the heart of the Alexa ecosystem.
As an applied scientist, you will advance state of the art techniques in ML and LLM, and work closely with product and engineering teams to build the next generation of the Alexa smart assistant.
Key job responsibilities
- Rapidly prototype ML/LLM solutions, evaluate feasibility, and drive projects to production deployment
- Continuously monitor and improve model performance through retraining, parameter tuning, and architecture refinements
- Develop new training and inference techniques to improve model performance
- Work cross-functionally across engineering, product, and business teams to understand customer needs, scope science work, and drive science solutions from conception to customer delivery
- Research and develop LLM innovations, and lead paper publications.
- Code proficiently in Python (required) and Java (preferred); optimize systems for high performance at scale; contribute code directly into production services
- Innovate and develop science and engineering solutions that optimize team operations and increase team effectiveness.
- Clearly communicate complex technical concepts to non-technical stakeholders and leadership