2026 - Senior/Staff Machine Learning Engineer - Multimodal Content Intelligence - Permanent
On-siteDublin, Leinster, Ireland
Job Summary
Lead development of video understanding and multimodal frameworks for semantic interpretation and narrative reasoning within the Terminal Cloud Technology Lab. Design tagging taxonomies, classification systems, and knowledge graphs to transform raw content into structured signals for the recommendation engine. Provide technical leadership by unblocking colleagues on complex challenges and driving end-to-end execution of high-performance systems. Stay ahead of state-of-the-art research in Vision-Language Models, independently evaluating and prototyping techniques for production deployment. Collaborate with cross-functional teams to integrate advanced content signals into discovery pipelines.
Required Qualifications
- Master's or PhD in Computer Science, AI, Machine Learning, or a related field
- 5–8+ years of professional experience in AI/ML research or advanced engineering
- Deep, hands-on experience with video understanding, temporal modeling, and Multimodal Large Language Models (MLLMs/VLMs), including fine-tuning, post-training or adapting these models for production use cases
- Expert proficiency in PyTorch, TensorFlow, or JAX
- Proven track record of deploying large-scale AI models in production environments
- Demonstrated ability to identify, evaluate, and rapidly adapt state-of-the-art techniques (from research papers, open-source releases, or industry advances) into working solutions that address real business needs
Desired Qualifications
- Contributions to high-impact projects or publications in top-tier conferences (e.g., CVPR, ICCV, NeurIPS)
- Experience with content quality assessment, news stream analysis, or semantic modeling
- Familiarity with high-level semantic modeling (e.g., emotion recognition, contextual reasoning), temporal action localization/scene segmentation, and computational aesthetics or visual quality assessment
- Experience leading engineers through complex technical challenges, for example as a technical lead on a project or workstream
- Experience presenting or mentoring within research communities, such as workshop talks, internal tech shares, or open-source maintainership
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