Amazon is looking to build Generative AI solutions on complex business problems that have significant global benefit. The Brand Protection Science team designs and builds highly performing and scalable AI models using machine learning, deep learning, LLM/Gen AI to identify and prevent infringement abuse and counterfeit on behalf of buyer, seller and brand owners worldwide.
Requirements
- Knowledge of machine learning approaches and algorithms
- Knowledge of ML, NLP, Information Retrieval and Analytics
- 5+ years of building machine learning models or developing algorithms for business application experience
- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
- Experience with deep learning libraries such as PyTorch, TensorFlow, MxNet
- Research publications in computer vision, deep learning or machine learning at peer-reviewed workshops, conferences or journals
Responsibilities
- lead a group of highly talented scientists, and partner with Tech, Business and Operations, to build the strategic vision for brand protection, drive execution and launch scalable AI solutions operating on billions of Amazon product listings WW for Brand Protection.
- lead a team of Applied Scientist to work backwards from customer needs and solve complex scientific problems that have a high business and customer impact.
- thought leader for inventing novel science solutions using SOTA ML techniques including LLM and GenAI.
- partner with your stakeholders and leadership to define the science vision and strategies for your team.
- accountable for the science vision and strategic direction of your team, the artifacts they provide, and any technologies owned.
- establish structures that enable your team to consistently deliver.
- lead your team to leverage the broader Amazon scientific community, and build a team culture that focuses on bringing research to production, removing road blockers, and delivering more results for Amazon customers.
Other
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 4+ years of building machine learning models or developing algorithms for business application experience
- 2+ years of scientists or machine learning engineers management experience
- excellent communication skills to explain complex scientific approaches to a variety of stakeholders and customers, and bridge the gap between science, tech, and business
- strategic about the team members' growth and provide those interested with opportunities to demonstrate higher level role scope, impact, complexity and leadership.
- Experience with the Scrum methodology (or similar alternatives) for agile software development
