Overview
As Microsoft continues to lead the way in AI innovation, Clipchamp is at the forefront of transforming how people create and share video content. We are the go-to video platform with a simple mission: to empower anyone to tell stories worth sharing. With nearly one hundred million registered users worldwide, we’re just getting started.
We are looking for an Applied Scientist to join our team through Microsoft’s University Recruiting program and help us explore the future of AI-powered video creation. As an Applied Scientist at Microsoft, you’ll have the opportunity to work with cutting-edge generative AI models, computer vision, multimodal models, AI tooling and research, applying your knowledge to real-world product challenges at scale.
You’ll work alongside experienced applied scientists, engineers, product experts and researchers to experiment with AI technologies, evaluate and improve model quality and develop intelligent solutions that make video creation simpler and more powerful. From improving AI-generated video experiences to exploring new approaches to editing and storytelling, you’ll have the opportunity to learn, experiment and contribute to products used by millions of people around the world.
You’ll join a nimble, cross-disciplinary team within Microsoft, working alongside engineers, product managers, designers, applied scientists and researchers. If you’re excited about building your career in applied AI, tackling challenging technical problems and exploring how emerging AI technologies can transform creative experiences, we’d love to hear from you.
Responsibilities
- Work with Applied Scientists, Engineers, Product Managers and Researchers to apply state-of-the-art AI and machine learning techniques to real-world product challenges in AI-powered video creation.
- Research and experiment with emerging approaches across generative AI, multimodal models, computer vision and machine learning that can improve product quality, performance and user experiences.
- Help develop, adapt and evaluate machine learning models for use in production scenarios, iterating on model performance and applying learnings to products used by millions of customers.
- Contribute to building data- and evaluation-backed solutions, using experimentation, quantitative analysis and quality evaluation to understand model behaviour, validate assumptions and measure improvements.
- Work with and create datasets used for training, experimentation and evaluation, including reviewing data quality, preparing data for modelling and helping identify opportunities to improve the quality and representativeness of datasets.
- Support the development of evaluation approaches and tools to measure the quality, reliability and performance of AI-powered experiences, helping teams understand where models perform well and where further improvements are needed.
- Collaborate and consult with Engineering teams to help bring researc
