We believe that the next 10x efficiency improvements in deep learning will come from better use of data. Good data curation allows you to train better models much more quickly, saving compute costs and accelerating research velocity. Our team has pioneered deep learning data research, built startups, and created tools for enterprise ML.

We have raised over $11.5M from top-tier investors including Amplify Partners, Radical Ventures, Conviction Capital, Jeff Dean, Yann LeCun, Geoff Hinton, and Adam D’Angelo to help make our vision a reality.

Learn more about the company here.

This role is based in Redwood City, CA. We are in person 5 days per week and offer relocation assistance to new employees. We provide visa sponsorship for candidates selected for this role.

About the Role

As a Research Intern at DatologyAI, you will conduct research investigating how intervention on training data can improve the quality and shape the behavior of deep learning models. Here is what your day-to-day would look like:

1. Transform messy literature into practical improvements. The research literature is vast, ambiguous, and constantly evolving. You will use your skills as a scientist to source, vet, implement, and improve promising ideas from the literature and your own creation.

2. Perform High-Risk, High-Reward Research. We want our interns to focus on problems that have massive potential to transform how data is ingested into future ML models. Rather than making incremental changes to current algorithms, we want you to work on novel project ideas that could change how we view data.

3. Conduct science driven by real-world needs. At DatologyAI, we understand that conference reviewers and academic benchmarks don’t always incentivize the most impactful research. Concrete customer needs and product improvements will guide your research.

4. Science is more than just experiments. We expect our Research Scientist Interns to collaborate closely with engineers, talk to customers, and shape the product vision

About You

Ideal candidates should have strong coding skills with experience with one of the following:

1. We would like to hire students with practical experience and/or publications related to any of the following research topics:

   1. Data research

      1. Data pruning/curation

      2. Curriculum learning

      3. Synthetic data generation

      4. Dataset distillation

      5. Effects of training data on model behavior

   2. Embedding models

   3. Semantic search

   4. Efficient ML

2. We would love to have you if you have practical experience and/or publications related to training large vision (especially video), language, and multimodal models.

3. Or teach us something new that you are passionate about that could improve data curation!