Sr. Applied Scientist, Amazon Ads Marketing Decision Science

The Ads Marketing Decision Science team builds intelligent data-driven systems that transform advertiser experiences through precise personalization and automated optimization. We decode complex patterns in advertiser behavior content effectiveness and performance signals to power real-time contextual marketing decisions at scale moving Amazon Ads from rules-based relevancy to true AI-driven personalization. Our work spans four pillars: Advertiser DNA (behavioral fingerprinting to predict advertiser needs and growth opportunities) Content Intelligence (frameworks to evaluate select and generate marketing content aligned to advertiser context) Automated Decision Systems (ML-powered audience targeting and next-best-action recommendations) and Gen-AI Applications (contextual natural interactions across marketing touchpoints).
As a Senior Applied Scientist on the team you will be at the forefront of our Gen-AI applications leading the science behind conversational and agentic experiences that help advertisers grow. This role demands a strong foundation in machine learning and in LLM/NLP deep fundamentals that you apply to build robust production-grade systems rather than treating models as black particular you will own the development of our chatbot capability designing the agentic reasoning retrieval and evaluation systems that make these interactions accurate helpful and trustworthy. You will set the technical vision innovate on behalf of our customers and take solutions end-to-end from inception to production. You will partner closely with engineering to deploy at scale and low latency and with product and business teams to ensure the experience meets real advertiser needs.


Key job responsibilities
Lead the design and development of the chatbot/agentic AI capability for WeChat and other third-party channels from concept through production.
Bring strong ML and LLM/NLP fundamentals to bear on system design grounding architecture and modeling choices in a deep understanding of the underlying methods.
Architect and build agentic AI systems planning tool use and multi-step reasoning grounded in Retrieval-Augmented Generation (RAG) over Amazon Ads knowledge sources.
Apply reinforcement learning and model fine-tuning (e.g. instruction tuning RLHF/RLAIF preference optimization) to adapt large language models to our domain and channels.
Define and operationalize rigorous LLM evaluation: golden sets faithfulness/groundedness precision/recall and human-in-the-loop evaluation mechanisms that reliably measure and improve quality.
Own applied engineering quality of the science stack PyTorch modeling well-designed APIs and latency/cost optimization for real-time production-grade interactions.
Collaborate with engineering product management and business teams to define requirements and ship measurable customer impact.
Drive continuous improvement through experimentation iterative development testing and optimization.
Translate complex scientific challenges into clear impactful solutions for business stakeholders.
Mentor and guide junior scientists fostering a collaborative high-performing team culture and engage the broader scientific community through presentations publications and patents.

About the team
We are a team of Applied Scientists Research Scientists Data Scientists and Business Intelligence Engineers with deep expertise in ML NLP Gen-AI RL and causal inference from a diverse range of backgrounds. We partner closely with strong engineers product managers and sales leaders who bring ads-industry depth and experience building scalable modeling and software solutions.

- 3 years of building machine learning models for business application experience
- PhD or Masters degree and 6 years of applied research experience
- Experience programming in Java C Python or related language
- Experience with neural deep learning methods and machine learning

- Experience with modeling tools such as R scikit-learn Spark MLLib MxNet Tensorflow numpy scipy etc.
- Experience with large scale distributed systems such as Hadoop Spark etc.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at NY New York - 183800.00 - 248700.00 USD annually