At DatologyAI, we are redefining the way enterprises train their machine learning models. Traditional methods involve training on random samples of data, which can be both inefficient and detrimental to model quality. Our pioneering research shows that smarter data selection significantly enhances model performance and reduces costs. We’ve transformed this research into cutting-edge tools that help businesses identify the optimal data for training, resulting in better models at a lower cost.
Founded by experts in deep learning research, startup creation, and enterprise ML tools, DatologyAI has quickly established itself as a leader in the field. Our recent funding includes a $46M Series A round led by Felicis Ventures, with support from Radical Ventures, Amplify Partners, Microsoft, Amazon, and renowned figures like Jeff Dean, Geoff Hinton, Yann LeCun, and Elad Gil. With over $57.5M in total funding, we’re scaling rapidly to revolutionize data curation across various modalities. Join us in pushing the boundaries of AI innovation!
About the Role
Summer 2024 Status
Please note that our Research Intern role for Summer 2024 is currently closed due to capacity constraints. However, we are still accepting applications for Fall and Winter internships!
Role Overview
As a Research Intern at DatologyAI, you will be at the forefront of exploring how interventions in training data can significantly enhance the quality and behavior of deep learning models. Your daily responsibilities will include:
Transforming Literature into Practical Solutions: Navigate through vast and evolving research literature to implement and refine promising ideas, both from existing studies and your own innovative approaches.
Conducting High-Risk, High-Reward Research: Tackle ambitious projects with the potential to revolutionize data ingestion processes for future ML models. We encourage bold, novel ideas that challenge the status quo.
Driving Science with Real-World Impact: Your research will be guided by concrete customer needs and product improvements, rather than purely academic benchmarks.
Collaborative Science: Work closely with engineers, engage with customers, and contribute to shaping the product vision. We value collaboration and expect our interns to integrate seamlessly into our dynamic team.
About You
We are looking for candidates who have a strong foundation in coding and experience in one or more of the following research areas:
Data Research and Curation
Data Pruning and Cleaning
Curriculum Learning
Synthetic Data Generation
Dataset Distillation
Effects of Training Data on Model Behavior
Embedding Models
Semantic Search
Efficient ML
Practical experience or publications related to training large vision models (especially video), language models, or multimodal models will be highly valued. We also welcome candidates who are passionate about data curation and can bring new, innovative ideas to our team.
Are you ready to make an impact in the world of AI? Apply now and be part of our journey to redefine data curation and machine learning!
Comments