Research Data Scientist
3 weeks ago
DatologyAI is a pioneering company in the field of deep learning data research. We've developed tools that enable enterprise customers to identify the right data on which to train, resulting in better models for cheaper. Our team has a strong background in building startups and creating tools for enterprise ML.
We've raised a $46M Series A led by Felicis Ventures, with investors including Radical Ventures, Amplify Partners, Microsoft, Amazon, and notable angels like Jeff Dean, Geoff Hinton, Yann LeCun and Elad Gil. With over $57.5M in total funding, we're rapidly scaling our team and compute resources to revolutionize data curation across modalities.
This role is based in Redwood City, CA, and we offer relocation assistance to new employees. We provide visa sponsorship for candidates selected for this role.
About the Role
This role is ideal for students with strong coding skills and experience in data research, data pruning/curation, curriculum learning, synthetic data generation, dataset distillation, effects of training data on model behavior, embedding models, semantic search, and efficient ML. We're looking for candidates who can conduct research investigating how intervention on training data can improve the quality and shape the behavior of deep learning models.
Responsibilities
As a Research Intern at DatologyAI, you will transform messy literature into practical improvements, perform high-risk, high-reward research, and conduct science driven by real-world needs. You will collaborate closely with engineers, talk to customers, and shape the product vision. We expect our Research Scientist Interns to have a strong understanding of machine learning concepts and be able to implement novel project ideas that could change how we view data.
About You
We're looking for students with practical experience and/or publications related to the mentioned research topics. If you have a passion for teaching us something new that could improve data curation, we'd love to hear from you. Our ideal candidate should have strong coding skills with experience in one of the following: data research, data pruning/curation, curriculum learning, synthetic data generation, dataset distillation, effects of training data on model behavior, embedding models, semantic search, and efficient ML.
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