Amazon Verified
E-commerce
Applied Scientist II, Prime AI/ML Science
Seattle, WAOnsiteFull Time$142,800–$193,200 /yrPosted 2 months agoVisa sponsorship available
Required skills
- modeling
- customer behavior
- machine learning
- artificial intelligence
- data mining
- TB scale data
- customer experience
- personalization
- subscription optimization
- GenAI/LLM
Nice to have
- Unix/Linux
- professional software development
Role summary
Amazon is seeking an Applied Scientist II for its Prime AI/ML Science team in Seattle. This role focuses on modeling customer behavior using machine learning, AI, and data mining on large-scale data to optimize the customer experience for Amazon Prime. Responsibilities include developing and applying ML models, optimizing GenAI/LLM solutions for personalization, building foundation models, and integrating with measurement systems. The scientist will leverage techniques like deep learning, transformers, and reinforcement learning, and work with AWS technologies. The position requires a PhD or Master's degree with 4+ years of experience in CS, ML, or related fields, and 3+ years of experience building models for business applications. Programming experience in Python, Java, or C++ is necessary, along with expertise in algorithms, data structures, numerical optimization, and data mining.
Interested in modeling and understanding customer behavior through machine learning, artificial intelligence, and data mining over TB scale data with huge business impact on millions of customers? Join our team of Scientists developing models to model customer behavior and optimize the customer experience with Amazon Prime. This includes understanding who our customers are, long-term value of the Prime membership program, and creating the right personalized framework for content and subscription optimization. As an AI/ML expert, you will partner directly with product owners to intake, build, and directly apply your modeling solutions.
There are numerous scientific and technical challenges you will get to tackle in this role, such as optimizing/fine-tuning GenAI/LLM solutions for Prime personalization, building GenAI foundation models, global scalability of models, combinatorial optimization, cold start problem, accelerated experimentation, short/long term goals modeling, and multi-step optimization leading to reinforcement learning of the customer journey. We employ techniques from GenAI/LLMs, supervised/semi-supervised learning, deep learning, transformer architectures, using outcomes from causal Econometric modeling, and Reinforcement learning.
As the central science team within Prime, our expertise gets routinely called upon to weigh in on a variety of topics. We also emphasize the need and value of scientific research and have developed a strong publication and patent record (internally/externally) which you will be a part of.
You will also utilize and be exposed to the latest in ML technologies and infrastructure: AWS technologies (EMR/Spark, Sagemaker, DynamoDB, S3, ClaudeCode), various AI/ML algorithms and techniques (Deep Learning, GenAI/LLMs, transformers, supervised/unsupervised/semi-supervised/reinforcement learning), and statistical modeling techniques.
- Stay abreast of current literature in the field and advance/build novel science solutions leveraging SoTA solutions.
- Build and develop AI/ML models and supporting infrastructure at TB scale, in coordination with software engineering teams.
- Leverage Deep Learning and GenAI solutions for building foundation models and personalized optimization solution.
- Develop offline policy estimation tools and integrate with measurement systems/econometric models.
- Establish scalable, efficient, automated processes for large scale data analyses, science development, science validation and model implementation.
- Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes.
- Work closely with the business to understand their problem space, identify the opportunities and formulate the problems.
- Use AI/machine learning, data mining, statistical techniques and others to create actionable, meaningful, and scalable solutions for the business problems.
- Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems.
Key job responsibilities
- Stay abreast of current literature in the field and advance/build novel science solutions leveraging SoTA solutions.
- Build and develop AI/ML models and supporting infrastructure at TB scale, in coordination with software engineering teams.
- Leverage Deep Learning and GenAI solutions for building foundation models and personalized optimization solution.
- Develop offline policy estimation tools and integrate with measurement systems/econometric models.
- Establish scalable, efficient, automated processes for large scale data analyses, science development, science validation and model implementation.
- Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes.
- Work closely with the business to understand their problem space, identify the opportunities and formulate the problems.
- Use AI/machine learning, data mining, statistical techniques and others to create actionable, meaningful, and scalable solutions for the business problems.
- Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems.
Basic Qualifications: - 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Preferred Qualifications: - Experience using Unix/Linux
- Experience in professional software development
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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
There are numerous scientific and technical challenges you will get to tackle in this role, such as optimizing/fine-tuning GenAI/LLM solutions for Prime personalization, building GenAI foundation models, global scalability of models, combinatorial optimization, cold start problem, accelerated experimentation, short/long term goals modeling, and multi-step optimization leading to reinforcement learning of the customer journey. We employ techniques from GenAI/LLMs, supervised/semi-supervised learning, deep learning, transformer architectures, using outcomes from causal Econometric modeling, and Reinforcement learning.
As the central science team within Prime, our expertise gets routinely called upon to weigh in on a variety of topics. We also emphasize the need and value of scientific research and have developed a strong publication and patent record (internally/externally) which you will be a part of.
You will also utilize and be exposed to the latest in ML technologies and infrastructure: AWS technologies (EMR/Spark, Sagemaker, DynamoDB, S3, ClaudeCode), various AI/ML algorithms and techniques (Deep Learning, GenAI/LLMs, transformers, supervised/unsupervised/semi-supervised/reinforcement learning), and statistical modeling techniques.
- Stay abreast of current literature in the field and advance/build novel science solutions leveraging SoTA solutions.
- Build and develop AI/ML models and supporting infrastructure at TB scale, in coordination with software engineering teams.
- Leverage Deep Learning and GenAI solutions for building foundation models and personalized optimization solution.
- Develop offline policy estimation tools and integrate with measurement systems/econometric models.
- Establish scalable, efficient, automated processes for large scale data analyses, science development, science validation and model implementation.
- Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes.
- Work closely with the business to understand their problem space, identify the opportunities and formulate the problems.
- Use AI/machine learning, data mining, statistical techniques and others to create actionable, meaningful, and scalable solutions for the business problems.
- Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems.
Key job responsibilities
- Stay abreast of current literature in the field and advance/build novel science solutions leveraging SoTA solutions.
- Build and develop AI/ML models and supporting infrastructure at TB scale, in coordination with software engineering teams.
- Leverage Deep Learning and GenAI solutions for building foundation models and personalized optimization solution.
- Develop offline policy estimation tools and integrate with measurement systems/econometric models.
- Establish scalable, efficient, automated processes for large scale data analyses, science development, science validation and model implementation.
- Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes.
- Work closely with the business to understand their problem space, identify the opportunities and formulate the problems.
- Use AI/machine learning, data mining, statistical techniques and others to create actionable, meaningful, and scalable solutions for the business problems.
- Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems.
Basic Qualifications: - 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Preferred Qualifications: - Experience using Unix/Linux
- Experience in professional software development
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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t 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 https://amazon.jobs/en/benefits.
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
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