Lead AI Scientist, Personalization & Discovery at Scale

Amazon; Sunnyvale (CA); On-site; USD 228,700 - 309,400; Full time

Benefits offered by this job

Health insurance and RSUs

401(k) matching

Paid time off

Parental leave

Comprehensive benefits

Job summary

Amazon is seeking a Principal Applied Scientist for Prime Video to lead the design, development, and deployment of advanced AI systems that power personalized experiences for millions of global customers. The role combines deep ML expertise with strategic leadership to guide end-to-end systems from foundational research to production deployment.

You will mentor scientists, influence product and engineering roadmaps, and publish impactful work.

Qualifications

• PhD or Master’s with 10+ years in ML/CS/stats or related field.
• 8+ years designing, building, deploying ML models at scale.
• Proven cross-functional leadership across ML/AI initiatives from ideation to production.
• Proficient in Python, Java, or C++, with TensorFlow or PyTorch experience.
• Deep expertise in recommendation systems, search relevance, or large-scale personalization.

Responsibilities

• Invent, prototype, and productionize large-scale AI solutions across PV’s personalization/discovery ecosystem.
• Provide technical leadership and influence product vision with engineers and PMs.
• Design and lead high-impact A/B tests and data analyses to inform product direction.
• Mentor scientists and engineers; drive cross-team collaboration and reviews.
• Stay ahead of trends; evolve long-term strategy and architecture.
• Publish impactful research internally and externally.

Skills

Leadership

ML model deployment

Python/Java/C++

Recommendation systems

Education

PhD or Master’s with 10+ years

Tools

Hadoop

Spark

Job description

Amazon is seeking a Principal Applied Scientist for Prime Video to lead the design, development, and deployment of advanced AI systems that power personalized experiences for millions of global customers. The role combines deep ML expertise with strategic leadership to guide end-to-end systems from foundational research to production deployment.

You will mentor scientists, influence product and engineering roadmaps, and publish impactful work.