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Applied Scientist, Alexa Daily Essentials
2 months ago
At Amazon, we're revolutionizing the way people interact with technology. As an Applied Scientist on the Alexa Daily Essentials team, you'll play a critical role in developing innovative language models that enhance Alexa's capabilities.
We're seeking a talented researcher to join our team and contribute to the development of cutting-edge AI technologies. If you're 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. You'll work closely with product and engineering teams to build the next generation of the Alexa smart assistant.
Key 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
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 2+ years of building machine learning models for business application experience
- Experience implementing algorithms using both toolkits and self-developed code
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- 3+ years of hands-on predictive modeling and large data analysis experience
- Experience using Unix/Linux
- Experience in professional software development
