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Sr. Applied Scientist, Support Products & Services

Job ID: 2694077 | Services LLC


Are you fascinated by the power of Natural Language Processing (NLP) and Large Language Models (LLM) to transform the way we interact with technology? Are you passionate about the use of Generative AI to build an advertiser facing solution that predict problems and coach users while they solve real word problems? If so, Amazon's Support Product & Services (SP&S) team has an exciting opportunity for you as an Applied Scientist.

Key job responsibilities
• Apply your expertise in LLM models to design, develop, and implement scalable machine learning solutions that address complex language-related challenges in the advertising support center domain.
• Use Transformers and apply other NLP techniques like Sentence embeddings, Dimensionality reduction, clustering and topic modeling to identify customer intents and utterances.
• Use services like AWS Lex, AWS Bedrock etc. to develop advertising facing solutions
• Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful solutions.
• Automating feedback loops for algorithms in production.
• Setup and monitor alarms to detect anomalous data patterns and perform root cause analyses to explain and address them.
• Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences.

A day in the life
You will work closely with a cross functional team of Software Engineers, Product Owners, Data Scientists, and Contact Center experts. You will research and investigate the latest options in industry to apply machine learning and generative AI to real world problems. You will work backwards from customer problems and collaborate with stakeholders to determine how to scale new technology and integrate with complicated help channels used by advertisers everyday.

About the team
SP&S team provides solutions and libraries that are leveraged by teams all across Amazon Advertising to provide timely and personalized help. The team aims to predict Advertisers problems and proactively surface intelligent guidance to customers at the right time. As a AS, you will help the team to achieve its vision of building and implementing the next generation of Contact Center technology. You will build/leverage LLMs to train them on advertising support domain knowledge and work shoulder to shoulder with stakeholders to externalize to users in novel ways.


- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- 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.
- Extensive experience in NLP domain with prior experience with Transformers, Generative AI and LLMs

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.