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Job Description
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Sr. Applied Scientist, Support Products & Services
Job ID: 2694077 | Amazon.com 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 predicts problems and coaches users while they solve real world 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. Automate 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 every day.
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 an Applied Scientist, 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. BASIC QUALIFICATIONS
- 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. PREFERRED QUALIFICATIONS
- 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.
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Job ID: 2694077 | Amazon.com 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 predicts problems and coaches users while they solve real world 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. Automate 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 every day.
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 an Applied Scientist, 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. BASIC QUALIFICATIONS
- 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. PREFERRED QUALIFICATIONS
- 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.
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