Applied Science Manager, Advertising Trust
Technology, Data & Digital · Data, AI & Analytics · Data Science · Machine Learning · Artificial Intelligence
In short
Amazon Ads is seeking an Applied Science Manager to lead a team of scientists in building next-generation ML systems for content moderation. This role involves defining the science strategy for ads trust, owning end-to-end delivery of ML solutions, and mentoring team members to drive automation and defect metric improvements at scale.
Responsibilities
- Lead a team of applied scientists working across multimodal ML, large-scale retrieval systems, and generative AI.
- Define the science strategy for ads trust.
- Own end-to-end delivery of ML solutions: problem formulation, offline experimentation, online A/B testing, and production deployment.
- Build and grow scientists, including hiring, mentoring, and developing team members.
- Partner with engineering, product, and operations teams to translate science investments into measurable automation improvements.
- Communicate science strategy and results to senior leadership.
Requirements
- 8+ years of applied research experience.
- 4+ years of scientists or machine learning engineers management experience.
- 4+ years in managing a team of 5-15 members.
Desired Qualifications
- Experience building production ML systems at Internet scale, especially involving multimodal deep learning, generative AI, or large-scale retrieval.
- Track record of delivering automation or classification systems with measurable business impact.
- Experience with content moderation, trust & safety, or policy enforcement systems.
- Publications in top-tier ML/AI venues (NeurIPS, ICML, CVPR, KDD, ACL, AAAI).
- Experience with LLMs (fine-tuning, distillation, RLHF, prompt engineering).
- Demonstrated ability to define and drive science roadmaps that influence product and business strategy.
Benefits
- Inclusive culture empowers Amazonians to deliver the best results.
- Workplace accommodations available for individuals with disabilities.
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