Lead Applied Scientist - Personalization & GenAI Ads

Amazon Inc.; Seattle (WA); Presencial; USD 167.000 - 226.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Paid time off

Parental leave

RSUs

Descripción de la vacante

Amazon Inc. is seeking an Advanced Scientist for Prime Video Ads to lead ML-driven personalization and experimentation at scale.

You will own end-to-end research, develop production-ready models, and collaborate with product and engineering teams to deliver measurable impact for hundreds of millions of viewers. You will work on state-of-the-art ML and causal inference, with opportunities to explore Gen-AI techniques, and contribute to the design of scalable, low-latency systems in a fast-paced

Formación

• 5+ years of building ML models for business applications.
• PhD, or Master's degree and 6+ years of applied research experience.
• Experience programming in Java, C++, Python or related language.

Responsabilidades

• Lead the research and development of ML models that personalize advertising decisions for 100M+ customers across 100k+ titles, with production deployment in mind.
• Develop deep learning architectures (multi-task learning, embedding-based representations) for customer behavior prediction at scale.
• Design and analyze large-scale A/B experiments, applying causal inference techniques to measure and optimize the impact of ad strategies on customer engagement and monetization.
• Partner with engineering to ensure models meet production latency and scalability requirements.
• Collaborate with product managers to frame business problems as tractable ML problems and translate findings into product decisions.
• Shape the team’s scientific roadmap, identifying high-impact research directions.

Conocimientos

ML experience

Causal ML

Deep learning

Java/Python/C++

Educación

PhD or Master's +6 years applied research

Herramientas

Java

Python

C++

Descripción del empleo

Amazon Inc. is seeking an Advanced Scientist for Prime Video Ads to lead ML-driven personalization and experimentation at scale.

You will own end-to-end research, develop production-ready models, and collaborate with product and engineering teams to deliver measurable impact for hundreds of millions of viewers. You will work on state-of-the-art ML and causal inference, with opportunities to explore Gen-AI techniques, and contribute to the design of scalable, low-latency systems in a fast-paced