Machine Learning Scientist Intern

This internship will explore using Video Language Models (VLMs) to improve brand safety and suitability classification, focusing on the GARM framework. Current methods like keyword analysis struggle with the complex context of video and MUM underperforms in several segments. VLMs, combining visual and textual understanding, offer a solution.

The project will:

• Understand GARM: Review GARM's Brand Safety and Suitability Framework and its content categories.
• Explore VLMs: Investigate suitable VLM architectures and training datasets, addressing data bias.
• Evaluate Performance: Benchmark VLM performance against existing methods using GARM-defined metrics.
• Address Challenges: Consider computational cost, explainability, and potential attacks on VLM systems.

Expected Outcomes:

• Experimenting  of VLMs for brand safety within GARM.
• Development and evaluation of VLM-based classifiers.
• Identification of challenges and solutions for VLM deployment.
• A final research report/paper.

Benefits to IAS: Improved accuracy and efficiency in brand safety assessment.

Benefits to the Intern: Experience with VLMs, real-world machine learning application, research experience, and insights into digital advertising and brand safety. This internship offers a chance to contribute to a key area in digital advertising.

Duration: 3-6 months. Targeting 4 months, or times that would coincide with Irish internships

Alternative research proposal stubs:

• Develop out-of-distribution methods for foundational model embeddings 
• Quantisation - Evaluate and propose best technique to quantize MUM embedding

About Integral Ad Science

Equal Opportunity Employer:

IAS is an equal opportunity employer, committed to our diversity and inclusiveness. We will consider all qualified applicants without regard to race, color, nationality, gender, gender identity or expression, sexual orientation, religion, disability or age. We strongly encourage women, people of color, members of the LGBTQIA community, people with disabilities and veterans to apply.

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To learn more about us, please visit http://integralads.com/ 

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