Multimodal Content Intelligence Expert – Permanent

Multimodal Content Intelligence Expert – AI Systems & Recommendation

Position Overview

A global technology research organization is seeking a Multimodal Content Intelligence Expert to lead the development of next-generation AI systems for content understanding and recommendation.

This role combines technical leadership, research innovation, and system architecture. The focus is on building scalable multimodal intelligence systems that process and interpret video, audio, images, and text to enhance content discovery, recommendation quality, and user engagement.

The successful candidate will define long-term strategy, lead a high-performing AI team, and drive the integration of advanced multimodal models into production-scale systems.

Key Responsibilities

Technical Strategy & Framework Development

• Define and lead the development of multimodal content intelligence frameworks.
• Focus on high-level semantic understanding, narrative reasoning, and contextual interpretation across:
  • Video
  • Audio
  • Images
  • Text
• Establish long-term technical direction aligned with business and product goals.

System Architecture & Scalability

• Design and oversee large-scale systems for:
  • Automated content tagging and categorization
  • Semantic classification and indexing
• Replace manual workflows with AI-driven pipelines.
• Ensure scalability, robustness, and efficiency in production environments.

AI Innovation & Applied Research

• Leverage advanced multimodal and vision-language models to improve content understanding.
• Develop solutions for:
  • Open-vocabulary recognition and dynamic tagging systems
  • Content structure reconstruction and taxonomy evolution
  • Trend and popularity prediction based on content features
  • Automated content quality evaluation across diverse media types
• Integrate state-of-the-art research into production systems.

Team Leadership & Collaboration

• Build and mentor a team of AI researchers and engineers.
• Foster a culture of technical excellence, innovation, and collaboration.
• Work closely with global research, product, and engineering teams to align system capabilities with platform needs.

Evaluation & Continuous Improvement

• Define evaluation methodologies for content intelligence systems.
• Develop data pipelines and benchmarking strategies to measure system performance.
• Continuously refine models and systems based on feedback and experimental results.

Required Qualifications

• PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• 10+ years of experience in AI/ML research or advanced engineering roles.
• Strong expertise in multiple areas such as:
  • Multimodal learning (video, text, image, audio)
  • Video understanding and temporal modeling
  • Natural language processing and semantic analysis
  • Content classification, tagging, recommendation, or search systems
• Hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow, JAX).
• Experience working with multimodal or vision-language models.
• Proven experience building and deploying large-scale AI systems.
• Strong understanding of evaluation methods, data pipelines, and production systems.

Preferred Qualifications

• Strong research background with publications in top-tier AI conferences.
• Experience building large-scale content intelligence or tagging systems from the ground up.
• Deep interest in generative AI and multimodal foundation models.
• Experience integrating AI systems into recommendation or content discovery platforms.

Personal Attributes

• Visionary technical leader with strong system-level thinking.
• Ability to bridge cutting-edge research and production deployment.
• Strong leadership and mentoring capabilities.
• Excellent communication and cross-functional collaboration skills.
• Passion for innovation in AI-driven content understanding.