Applied Scientist - AI Brand Safety & Content Classification

Amazon Science; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Amazon Science is seeking an Applied Scientist to pioneer AI-powered brand safety and content classification across web, mobile, CTV, and audio inventory. You will lead real-time, low-latency ML systems that evaluate billions of signals and adapt to evolving content risks with generative AI at internet scale.

You will own the science strategy for LLM-powered classification, semantic understanding, and adaptive model resilience, collaborating with engineers to deploy scalable production systems

Qualifications

• PhD or a Master’s degree with experience in CS/CE/ML or related field
• Experience publishing in top-tier conferences or journals
• Experience programming in Java, C++, Python or related language
• Experience in algorithms, data structures, numerical optimization, data mining, parallel/distributed computing
• Experience building ML models for business applications

Responsibilities

• Own the science strategy for AI-powered brand safety classification
• Build LLm-powered content classification systems with billions of decisions/day at millisecond latency
• Develop multimodal evaluation pipelines across text, images, audio, and video in real time
• Design adaptive ML systems resilient to adversarial evolution and contextual brand risk
• Define measurement frameworks and drive continuous improvement
• Translate research into production — prototype to deployed model
• Publish at peer-reviewed venues in adversarial ML, NLP, content safety
• Collaborate with software teams to integrate experiments into large-scale Amazon production systems

Skills

Programming in Java/C++/Python

ML model development

Academic publications

Algorithms and data structures

High-performance computing

Education

PhD or Master in CS/CE/ML

Tools

Unix/Linux

Job description

Amazon Science is seeking an Applied Scientist to pioneer AI-powered brand safety and content classification across web, mobile, CTV, and audio inventory. You will lead real-time, low-latency ML systems that evaluate billions of signals and adapt to evolving content risks with generative AI at internet scale.

You will own the science strategy for LLM-powered classification, semantic understanding, and adaptive model resilience, collaborating with engineers to deploy scalable production systems