Senior Applied Scientist, Amazon Fulfillment and Packaging Technology
Senior Applied Scientist, Amazon Fulfillment and Packaging Technology
Posted on :
29-05-2025
Employer Active
1 Vacancy
Job Alert
You will be updated with latest job alerts via emailValid email field required
Send jobs
Share
Send me jobs like this
Job Alert
You will be updated with latest job alerts via emailValid email field required
Send jobs
Job Description
Do you want to be part of a team thats revolutionizing Amazons fulfillment and packaging technology Can you commit to optimizing systems that process tens-of-millions of customer packages daily with the lowest cost to serve and a defect-free customer experience Do you have a passion for solving complex science challenges and building a sustainable e-commerce experience
Your Reinforcement Learning skills can help make that a reality on the Mechatronics and Sustainable Packaging team. We are looking for a talented Senior Applied Scientist to join our team. You will join a team of Scientists and Machine Learning Engineers (MLEs) to directly improve the packaging experience of Amazon customers in the fulfillment technology space. The team consists of experts in the field of Statistics Operational Research Machine Learning (ML) Computer Vision and Generative AI who work together to break new ground in the world of automated packaging solutions.
Youll work in a collaborative environment where you will deploy and scale ML solutions to peta-bytes of data work on problems that havent been solved before and understand whether they succeed via statistically relevant experiments across millions of customers. Youll see the work you do directly improve the packaging experience of Amazon customers in the fulfillment technology space. If you are interested in robotics computer vision machine learning big data and building scalable solutions this role is for you.
The successful candidate will have a PhD in Computer Science Statistics or Engineering with a strong focus on reinforcement learning Deep learning generative AI or a related field and 5 years of practical experience solving complex problems in computer vision anomaly detection robotics. or multi-modal classification systems. Manufacturing packaging and/or logistic experience is a plus but not a requirement.
Key job responsibilities
- Advance exploratory research projects in machine learning statistics and related fields to create defect-free packaging customer experiences
- Analyze large amounts of Amazon shipments to discover patterns find opportunities and develop highly innovative scalable algorithms to seize these opportunities
- Validate new or improved models via statistically relevant experiments across millions of customers
- Work closely with software engineering teams to build scalable prototypes for testing and integrate successful models and algorithms in production systems at very large scale
- PhD in engineering technology computer science machine learning robotics operations research statistics mathematics or equivalent quantitative field or Masters degree and 6 years of industry or academic research experience
- 5 years of building machine learning models or developing algorithms for business application experience
- Experience programming in Java C Python or related language
- Experience in applied research
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience applying theoretical models in an applied environment
- Proven track record of bringing advanced science solutions to production
- Professional experience building complex software systems especially involving deep learning machine learning robotics and/or computer vision that have been successfully delivered to customers
- Algorithm and model development experience for large-scale applications
- Ability to handle multiple contending priorities in an energizing environment
- Strong problem solving skills
- Solid software development experience
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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150400/year in our lowest geographic market up to $260000/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.
Your Reinforcement Learning skills can help make that a reality on the Mechatronics and Sustainable Packaging team. We are looking for a talented Senior Applied Scientist to join our team. You will join a team of Scientists and Machine Learning Engineers (MLEs) to directly improve the packaging experience of Amazon customers in the fulfillment technology space. The team consists of experts in the field of Statistics Operational Research Machine Learning (ML) Computer Vision and Generative AI who work together to break new ground in the world of automated packaging solutions.
Youll work in a collaborative environment where you will deploy and scale ML solutions to peta-bytes of data work on problems that havent been solved before and understand whether they succeed via statistically relevant experiments across millions of customers. Youll see the work you do directly improve the packaging experience of Amazon customers in the fulfillment technology space. If you are interested in robotics computer vision machine learning big data and building scalable solutions this role is for you.
The successful candidate will have a PhD in Computer Science Statistics or Engineering with a strong focus on reinforcement learning Deep learning generative AI or a related field and 5 years of practical experience solving complex problems in computer vision anomaly detection robotics. or multi-modal classification systems. Manufacturing packaging and/or logistic experience is a plus but not a requirement.
Key job responsibilities
- Advance exploratory research projects in machine learning statistics and related fields to create defect-free packaging customer experiences
- Analyze large amounts of Amazon shipments to discover patterns find opportunities and develop highly innovative scalable algorithms to seize these opportunities
- Validate new or improved models via statistically relevant experiments across millions of customers
- Work closely with software engineering teams to build scalable prototypes for testing and integrate successful models and algorithms in production systems at very large scale
- PhD in engineering technology computer science machine learning robotics operations research statistics mathematics or equivalent quantitative field or Masters degree and 6 years of industry or academic research experience
- 5 years of building machine learning models or developing algorithms for business application experience
- Experience programming in Java C Python or related language
- Experience in applied research
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience applying theoretical models in an applied environment
- Proven track record of bringing advanced science solutions to production
- Professional experience building complex software systems especially involving deep learning machine learning robotics and/or computer vision that have been successfully delivered to customers
- Algorithm and model development experience for large-scale applications
- Ability to handle multiple contending priorities in an energizing environment
- Strong problem solving skills
- Solid software development experience
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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150400/year in our lowest geographic market up to $260000/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.
Required Experience:
Senior IC
Employment Type
Full-Time
Key Skills
Report This Job
Disclaimer: Drjobpro.com is only a platform that connects job seekers and employers. Applicants are advised to conduct their own independent research into the credentials of the prospective employer.We always make certain that our clients do not endorse any request for money payments, thus we advise against sharing any personal or bank-related information with any third party. If you suspect fraud or malpractice, please contact us via contact us page.
