Job Overview
Integral Ad Science (IAS) is a leading global media measurement and optimisation platform. IAS is hiring a Data Science Intern for the Multimedia Services (Embeddings & Agentic Systems) Team. The internship involves cutting‑edge ML projects on multimodal classification systems, including video, image, text, and audio.
Responsibilities
Build and evaluate machine learning models for multimodal content understanding.
Develop and analyse models for training, active learning, and large‑scale evaluation.
Run experiments with modern ML frameworks (PyTorch, TensorFlow, Hugging Face) and document findings.
Contribute to ML pipelines, tools for retrieval, embeddings, and automated annotation.
Collaborate with data scientists, ML engineers, and knowledge engineers to test new ideas and improve classification accuracy.
Present results, insights, and recommendations to the broader ML team.
Support ongoing research in semantic topic modelling, misinformation analysis, and trend detection.
Qualifications
Currently pursuing a degree in Computer Science, Machine Learning, Data Science, or a related field.
Experience with Python and data‑science libraries (NumPy, Pandas, Scikit‑learn).
Familiarity with a deep learning framework such as PyTorch or TensorFlow.
Interest in computer vision, NLP, audio processing, or multimodal modelling.
Ability to work with datasets, run experiments, and explain results clearly.
Curiosity, willingness to learn, comfort asking questions, strong analytical thinking, and attention to detail.
Preferred Skills
Experience with embeddings (CLIP, Whisper, BERT, etc.) or vector databases.
Hands‑on work with active learning, retrieval, or large‑scale ML pipelines.
Prior internship or project experience in applied machine learning.
Benefits & Salary
New York/California Applicants: Salary range is $XXXXX – $XXXXX. Actual pay may vary based on experience or geographic location.
Equal Opportunity Employer
IAS is an equal‑opportunity employer committed to diversity and inclusiveness. IAS considers all qualified applicants without regard to race, color, nationality, gender, gender identity or expression, sexual orientation, religion, disability, or age. IAS encourages women, people of color, LGBTQIA community members, people with disabilities, and veterans to apply.
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