Applied Science: PhD Internship Opportunities - Multiple Locations
Core
Analyze and improve performance of advanced algorithms on large-scale datasets, design experimental processes for iteration, and implement prototypes of scalable systems in AI applications.
Role type
PhD Intern, Applied Science (Machine Learning)
Builds
Scalable AI systems and prototypes for product scenarios
Domain
Machine Intelligence, Machine Learning, Large-scale Data
Deliverable
production ML models
Required skills
Experimental design, Data preparation, Large-scale distributed systems, Offline and online evaluation metrics, Research publications, Controlled experiments
Preferred skills
Search, Language models, Recommender systems, Geospatial or location intelligence, Content and commerce systems
Technologies
Large-scale distributed systems
Responsibilities
Analyze and improve performance of advanced algorithms on large-scale datasets, Design experimental process for iteration and optimization, Implement prototypes of scalable systems in AI applications, Prepare data to be used for analysis by reviewing criteria that reflect quality and technical constraints, Assist with the development of usable datasets for modeling purposes, Explore product challenges using state of the art solutions
Seniority
Intern
