About the job
The Brand Protection Science team designs and builds high performance AI systems using machine learning and deep learning that identify and prevent infringement and counterfeit on behalf of brand owners worldwide. We are looking for a highly talented scientist to help build of our AI vision for Brand Protection. As a applied scientist on the team, you will use STOA AI and ML techniques to understand and extract key information from product detail page, built automated AI solutions that thinks like human to make autonomous decisions. You will work backwards from data insights and customer feedback to build the right machine learning solutions, and resourceful in finding innovative solutions to unsolved problems. You will work closely will product team and engineering partners to launch the solution into production and own the end-to-end solution.
Responsibilities
Understand business challenges by analyzing data and customer feedback
Collaborate with tech and product teams on building ML strategies, experimentation, implementation and continuous improvement
Analyze and extract relevant information from large amounts of both structured and unstructured data to design strategies to solve business problems.
Use deep learning and machine learning techniques to create scalable solutions for business problems
Create business and analytics reports and present to the senior management teams
Research and implement novel AI solutions and publish research papers
Qualifications
Minimum
PhD, or Master's degree and 1+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience
Experience in patents or publications at top-tier peer-reviewed conferences or journals
Experience programming in Java, C++, Python or related language
Experience implementing algorithms using both toolkits and self-developed code
Preferred
extensive experience driving Machine Learning initiatives, specially in NLP and LLM applications, from conception to launch in a rapidly evolving environment. You will work closely with other scientists and enigneers to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems.