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Applied Scientist Ii, Amazon Beauty Tech
1 day ago
PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Hands-on experience in Machine Learning, Recommendation Systems (RecSys), Personalization, LLM-based RecSys, Search, Ranking, NLP, or related technologies
Technology is giving the beauty industry a makeover Are you interested to disrupt and redefine the way customers buy Beauty products online? Are you interested in using the latest advances in machine learning, computer vision, and big-data technologies to build online customer experiences for Beauty products that can equal or even surpass an in-store experience? Amazon Beauty is reinventing the shopping experience for all beauty customers across the largest selection of brands to become the most trusted beauty destination. Beauty is unique in retail with a diverse customer set along with products that are emotional, fun, and creative. This is your chance to get in on the ground floor to build something entirely new and transform an industry
To achieve our vision, we think big and tackle technological challenges every day. We need builders and disruptors who are not afraid to innovate Our architecture and development processes support rapid experimentation, global deployments, and self-service capabilities that allow us to scale better.
**We build**:
- Amazon scale systems: All our technology needs to work at Amazon scale, serving millions of customers with millisecond-level latency.
- Immersive customer experiences: We will create elevated and immersive customer experiences that using cutting-edge UI-technologies and user-centric design patterns.
- Computer Vision and augmented reality (AR) experiences: We bring exciting experiences directly to the customer's mobile phone using their cameras and combinations of computer vision and AR.
- Personalization using machine learning: We use latest advances in ML and GenAI to provide better-personalized shopping experiences.
- Data & analytics pipelines: Amazon is data-driven, and a robust data backbone is necessary for our systems. We build on core AWS services such as EC2, S3, DynamoDB, SageMaker, StepFunctions, etc.
Key job responsibilities
We are looking for talented and innovation-driven scientists who are passionate about leveraging the latest advances in Recommendation Systems (RecSys), Personalization algorithms, LLM-based RecSys, Search, Ranking, NLP, and related technologies, to solve customer problems in the Beauty space. You will have an opportunity to revolutionize the customer shopping experience across the world's most extensive catalog of beauty products. You will be directly responsible for leading the ideation, design, prototyping, development, and launch of innovative scientific solutions that address customer problem in the beauty and shopping space. You will closely partner with product managers, UX designers, engineers, and the broader Amazon scientific community to pioneer state-of-the-art solutions to extremely challenging problems in machine learning and RecSys. You will be our organization's Tech Evangelist and represent our organization in key internal and external AI, ML, or RecSys conferences.
About the team
Amazon Beauty Tech is a key and essential part of the Consumables organization and North America Stores. We are a passionate group of engineers, scientists, product managers, and designers who drive technological innovation to improve the customer shopping experience. We have a startup-like work culture where innovation is encouraged; we are never afraid to propose big ideas for fear of failing
Vancouver, BC, CAN
- 1+ years of solving business problems through machine learning, data mining and statistical algorithms experience
- Top tier AI publications is a strong plus
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, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.
