Applied Scientist II, Amazon Smart Vehicles

02 ott - Asti
Amazon

Applied Scientist II, Amazon Smart Vehicles
La preghiamo di verificare di possedere il livello di esperienza e le qualifiche adeguate leggendo la panoramica completa di questa occasione qui sotto.
The Amazon Smart Vehicles (ASV) science team is seeking a passionate and skilled Applied Scientist with extensive expertise in advanced LLM technologies. This role involves innovating in rapidly evolving areas of AI research, focusing on creating personalized services to enhance drivers' and passengers' experiences. Your work will aim to simplify their lives, keep them informed, entertained, productive, and safe on the road, with direct application to prominent Amazon products.
If you have extensive expertise in LLMs, natural language processing, and machine learning, along with experience in high-performing research teams, this could be the perfect opportunity for you. Our dynamic and fast-paced environment demands a high level of independence in decision-making and the ability to drive ambitious research initiatives through to production.




You will collaborate closely with other science and engineering teams, as well as business stakeholders, to ensure your contributions are both impactful and delivered with maximum efficiency.
Key job responsibilities
- Leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in generative artificial intelligence (GenAI)
- Work with talented peers to lead the development of novel algorithms and modeling techniques to advance the state of the art with LLMs
- Collaborate with other science and engineering teams as well as business stakeholders to maximize the velocity and impact of your contributions

About the team
This is an exciting moment to lead in AI research and application. As part of the Amazon Smart Vehicles science team, you have the opportunity to shape the future by enhancing information-driven experiences for Amazon customers around the globe. Your work will directly influence

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