About the Role
You will build production machine learning models on large-scale video and audio datasets, provide data-driven recommendations and actionable insights, and develop multifunctional learning pipelines. You will collaborate with product and engineering teams to deploy models at scale and train multimodal models using techniques such as RAG, self-supervised, semi-supervised, and transductive learning.
Requirements
- MSc or PhD student in Computer Science, Engineering, Statistics, Math, Physics, or advanced undergraduate
- Deep classroom experience in data science or machine learning or prior internship experience
- Comfortable with Python or R
- Knowledge of machine learning and deep learning algorithms (e.g., gradient boosting, CNNs, sequence models)
- Familiarity with frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn
- Knowledge of computer vision and natural language processing
- Experience with large multimodal and language models preferred
- Great communication skills and ability to multitask and work as a team player
- Ability to balance attention to detail with agile execution
Responsibilities
- Work with the AI Machine Learning and Data Science team
- Build production machine learning models on large-scale video and audio datasets
- Provide data-driven recommendations and actionable insights on content understanding, augmentation, and location
- Develop multifunctional learning pipelines
- Collaborate with product and engineering teams to deploy models at scale
- Train and develop multimodal learning models using RAG, self-supervised, semi-supervised, and transductive learning
Benefits
- Paid summer internship
- Catered lunches
- Summer party