About the position
In this internship position you will be a key member of the Data Science team. You will be responsible for scouting state of the art publications in different fields of machine learning and artificial intelligence. You will be working in the data processing pipeline as well as with our models.
- Helping in our research efforts, scouting for the state of the art publications in different fields of machine learning and artificial intelligence.
- Participating in the entire data processing pipeline, including: analysis, wrangling, preprocessing and feature engineering.
- Assisting in the design and development of our own inhouse models.
- Evaluating our models’ performance and committing to the implementation of potential improvements.
You are a highly enthusiastic Data Science student. You thrive in dynamic environments and are able to take initiative and enjoy challenges. You enjoy building and updating diverse data solutions at the same time, learning new tools as needs come up, and collaborating with scientists and clients in highly non-linear projects.
- Currently pursuing a Bachelor's degree in Data Science, Computer Science, Software Engineering, Mathematics, similar technical field of study or equivalent practical experience.
- Professional handling of Python and SQL.
- Demonstrable experience with machine learning models. Applicants are encouraged to share their Github profiles and personal projects.
- Proficiency in mainstream deep learning frameworks. Preferably Pytorch.
- Experience with cloud computing and GPU-accelerated environments. Preferably in the AWS ecosystem.
- Demonstrable experience working with state of the art deep learning architectures.
- Knowledge of the main components of a machine learning project pipeline, including: data wrangling, feature engineering, training and evaluation.
What we offer
- WFH with flexible work hours
- Early-stage startup equity
- Unlimited PTO
- Publication opportunities
- Science-driven culture
- Contacts within the Harvard / MIT ecosystem
- Yearly bonus for personal learning