Head of Applied Science @ Microsoft
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Job Details
Overview
Microsoft, through Clipchamp, is leading transformation in AI-powered video creation and consumption. The Head of Applied Science will set strategic direction, mentor a high-performing team, and turn advanced research into impactful product capabilities.
Responsibilities
- Stay at the forefront of AI, generative media, and LLM research using techniques such as prompt engineering, fine-tuning, and retrieval-augmented generation.
- Lead the design and deployment of advanced ML, NLP, and CV models to power intelligent video editing, generation, and personalization.
- Architect and optimize machine learning models to enhance video output quality and creativity.
- Develop and scale ranking systems for video discovery and recommendation.
- Design evaluation methodologies and iterate models using user feedback, telemetry, and A/B testing.
- Collaborate with engineering, product management, and design teams to integrate AI models into workflows.
- Provide technical leadership and mentor applied scientists and ML engineers.
- Recruit and nurture diverse talent while setting ambitious, creator-focused goals.
Qualifications
Required qualifications include an advanced degree or equivalent in a related field and extensive experience in research, machine learning, and people management. Deep expertise in LLMs, prompt engineering, fine-tuning, and retrieval-augmented generation is essential.
Other Requirements
Applicants must pass Microsoft-specific security screenings such as the Microsoft Cloud Background Check.
Preferred Qualifications
Preferred candidates will have extensive management experience, a track record of presenting at industry conferences, and a history of deploying production-scale AI systems.
Key Skills/Competency
- Artificial Intelligence
- Machine Learning
- LLM
- NLP
- Computer Vision
- Research
- Leadership
- Product Integration
- Data Analysis
- Model Evaluation
How to Get Hired at Microsoft
🎯 Tips for Getting Hired
- Customize your resume: Tailor achievements to AI and leadership roles.
- Highlight technical skills: Emphasize expertise in ML frameworks.
- Showcase research impact: Include real-world case studies.
- Prepare for behavioral interviews: Demonstrate team management experiences.