Role at a glance
- Salary
- $167.1K – $226.1K/yr
- Location
- Seattle, Washington, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Education
- PhD, or Master's degree
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Role Summary
This role develops machine learning and artificial intelligence solutions for Amazon Prime personalization and customer experience optimization using TB-scale business data. The scientist partners with product owners and software engineering teams to develop scalable models, experimentation and measurement systems, and optimization approaches for customer behavior and subscription outcomes.
What You'll Do
- Stay abreast of current literature and build novel science solutions leveraging state-of-the-art methods.
- 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 foundation models and personalized optimization.
- Develop offline policy estimation tools and integrate them with measurement systems and econometric models.
- Establish scalable, efficient, automated processes for large-scale data analysis, science development, validation, and model implementation.
- Analyze historical business data and design, develop, and evaluate models to understand and predict customer behavior.
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View full postingQualifications
Required
- 3+ years of building machine learning models for business application experience
- PhD, or Master's 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
Preferred
- 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.
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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 machine learning models for business application experience- PhD, or Master's 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
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.
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 - 167,100.00 - 226,100.00 USD annually
About the company
amazon
Large Enterprise
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.