Machine Learning Scientist Intern

at  Integral Ad Science

Integral Ad Science (IAS) is a global technology and data company that builds verification, optimization, and analytics solutions for the advertising industry and we’re looking for a Machine Learning Scientist (ML) Intern to join our Multimedia Core Service team in Dublin, Ireland. If you are excited by technology that has the power to handle hundreds of thousands of transactions per second; collect tens of billions of events each day; and evaluate thousands of data-points in real-time all while responding in just a few milliseconds, then IAS is the place for you!
As a ML Scientist Intern you will work on pushing the state of the art of our current Machine Learning systems focused on Video, Image, Audio and Text understanding. You will prototype, implement and evaluate deep learning methods including self-supervised methods, out-of-distribution (OOD) detection, metric learning, multimodality (vision, text and audio) and any other relevant strategies. This internship is an opportunity for you to gain practical experience with deep learning, interacting with large scale production environments and having the opportunity to research novel methods that can push the state of the art of media understanding and content evaluation.

What you’ll get to do:

• Prototype, implement and evaluate machine learning methods for videos. Main focus would be on self-supervised and multimodality methods but other approaches are possible.
• Conduct research and experiments to improve the accuracy and efficiency of the models.
• Work with the framework of your choice, e.g. PyTorch, TensorFlow, etc.
• Integrate machine learning models into production systems.
• Stay up-to-date with the latest advancements in the field of machine learning and contribute to knowledge sharing within the team.

YOU SHOULD APPLY IF YOU HAVE MOST OF THIS EXPERIENCE:

• Currently pursuing a Master’s or a PhD degree in Computer Science, Mathematics, Computer Engineering, Electrical Engineering, or a related field.
• Familiarity with machine learning and deep learning methods for one (or more) modality: vision, text, audio.
• Programming skills with languages such as Python and familiarity with libraries like NumPy, SciPy, Pandas, PyTorch and TensorFlow.
• Familiarity with at least one of the following methods: CNNs, ViT, LLMs, BeRT, Whisper, CLIP.
• Experience with Self-Supervised Learning methods is preferred.

• Prototype, implement and evaluate machine learning methods for videos. Main focus would be on self-supervised and multimodality methods but other approaches are possible.
• Conduct research and experiments to improve the accuracy and efficiency of the models.
• Work with the framework of your choice, e.g. PyTorch, TensorFlow, etc.
• Integrate machine learning models into production systems.
• Stay up-to-date with the latest advancements in the field of machine learning and contribute to knowledge sharing within the team