senior applied scientist, amazon customer service
Senior Applied Scientist, Amazon Customer Service
Job ID: | Services LLC
We see our customers as invited guests to a party, and we are the hosts. It's our job every day to make every important aspect of the customer experience a little bit better. - Jeff Bezos, Founder & CEO.
We didn't make Amazon a trillion-dollar company, our customers did and we want to ensure that our customers always have a positive experience that keeps them coming back to Amazon. To help achieve this, the Worldwide Defect Elimination (WWDE) team relentlessly focuses on maintaining customer trust by building products that offer appropriate resolutions to resolve issues faced by our customers. WWDE scientists solve complex problems and build scalable solutions to eliminate systemic defects and prevent future issues.
As a Sr. Applied Scientist, your role is pivotal in leveraging advanced AI and Machine Learning (ML) techniques to address customer issues at scale. You'll lead the development of innovative solutions that detect and organize issues, identify root causes, and route them to resolving teams across the company. You will leverage a spectrum of scientific techniques across both classical ML and Natural Language Processing (NLP)/GenAI to comb over our billions of customer interactions (using a combination of media). In this role, you will collaborate with cross-functional teams (Product, Engineering, Program) and contribute to advancing the state of defect elimination research.
Key job responsibilities
• Deliver solutions to the core business problems and influencing business partners
• Research and develop modeling techniques for NLP, DL, and ML
• Establish scientific culture and standards for all the scientists (publication, best practices, reviews, etc.)
• Develop scientific talent on the team
BASIC QUALIFICATIONS
• 5+ years of building deep learning or machine learning models for business application experience
• Master's degree in computer science, machine learning, statistics, mathematics or equivalent quantitative field
• Deep knowledge in one or more areas of machine learning or deep learning
• Proficient with common ML and DL frameworks such as PyTorch
• Experience programming in Java, Python or related language
PREFERRED QUALIFICATIONS
• PhD in computer science, machine learning, statistics, mathematics or equivalent quantitative field
• Experience in patents or publications at top-tier peer-reviewed conferences or journal
• Strong experience with NLP and generative deep learning models (i.e. LLM).
• Exceptional communication and collaboration skills
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.
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you If you're passionate about this role and want to make an impact on a global scale, please apply.
#J-18808-Ljbffr
Apply Now
Job ID: | Services LLC
We see our customers as invited guests to a party, and we are the hosts. It's our job every day to make every important aspect of the customer experience a little bit better. - Jeff Bezos, Founder & CEO.
We didn't make Amazon a trillion-dollar company, our customers did and we want to ensure that our customers always have a positive experience that keeps them coming back to Amazon. To help achieve this, the Worldwide Defect Elimination (WWDE) team relentlessly focuses on maintaining customer trust by building products that offer appropriate resolutions to resolve issues faced by our customers. WWDE scientists solve complex problems and build scalable solutions to eliminate systemic defects and prevent future issues.
As a Sr. Applied Scientist, your role is pivotal in leveraging advanced AI and Machine Learning (ML) techniques to address customer issues at scale. You'll lead the development of innovative solutions that detect and organize issues, identify root causes, and route them to resolving teams across the company. You will leverage a spectrum of scientific techniques across both classical ML and Natural Language Processing (NLP)/GenAI to comb over our billions of customer interactions (using a combination of media). In this role, you will collaborate with cross-functional teams (Product, Engineering, Program) and contribute to advancing the state of defect elimination research.
Key job responsibilities
• Deliver solutions to the core business problems and influencing business partners
• Research and develop modeling techniques for NLP, DL, and ML
• Establish scientific culture and standards for all the scientists (publication, best practices, reviews, etc.)
• Develop scientific talent on the team
BASIC QUALIFICATIONS
• 5+ years of building deep learning or machine learning models for business application experience
• Master's degree in computer science, machine learning, statistics, mathematics or equivalent quantitative field
• Deep knowledge in one or more areas of machine learning or deep learning
• Proficient with common ML and DL frameworks such as PyTorch
• Experience programming in Java, Python or related language
PREFERRED QUALIFICATIONS
• PhD in computer science, machine learning, statistics, mathematics or equivalent quantitative field
• Experience in patents or publications at top-tier peer-reviewed conferences or journal
• Strong experience with NLP and generative deep learning models (i.e. LLM).
• Exceptional communication and collaboration skills
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.
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you If you're passionate about this role and want to make an impact on a global scale, please apply.
#J-18808-Ljbffr
Apply Now