2026 - Senior/Staff Machine Learning Engineer - Multimodal Content Intelligence - Permanent

Location: Dublin, Ireland About Huawei Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. We are committed to bringing digital to every person, home and organization for a fully connected, intelligent… ## What you'll do be both a hands-on technical expert and a technical leader, advancing the SOTA in multimodal content understanding while guiding a small group of engineers through complex technical problems. Your work will be instrumental in enhancing our core recommendation engine, directly impacting product performance and user engagement through advanced content signals. Responsibilities - Drive Video & Multimodal Understanding: Lead the development of video understanding and implementation of multimodal frameworks for semantic understanding, narrative reasoning, and high-level content interpretation. - Build Structured Content Intelligence: Design and own tagging taxonomies, classification systems, and knowledge graph structures that turn raw multimodal content into structured, actionable signals. - Provide Technical Leadership: Serve as the technical point of contact for a small group within the team, unblocking colleagues on complex technical challenges and ensuring high-quality execution on shared initiatives. - Adopt New Technology: Stay ahead of state-of-the-art research in multimodal learning and VLMs, independently evaluating, prototyping, and bringing promising techniques from research to production. - Own Technical Execution: Drive end-to-end development of high-performance systems, resolving high-impact bottlenecks in accuracy, latency, and scalability. - Collaboration & Integration: Work closely with cross-functional teams to integrate content signals into production recommendation and discovery pipelines. Basic ## What you'll bring - Education: Master's or PhD in Computer Science, AI, Machine Learning, or a related field. - Experience: 5–8+ years of professional experience in AI/ML research or advanced engineering (industry experience preferred). - Video Understanding / VLM Expertise: 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. - Frameworks: Expert proficiency in PyTorch, TensorFlow, or JAX. - Production Skills: Proven track record of deploying large-scale AI models in production environments. - SOTA-to-Production: 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. ## Nice to have - Publications & Research Recognition: Contributions to high-impact projects or publications in top-tier conferences (e.g., CVPR, ICCV, NeurIPS). - NLP & Content Assessment: Experience with content quality assessment, news stream analysis, or semantic modeling. - Narrative & Aesthetics Analysis: Familiarity with high-level semantic modeling (e.g., emotion recognition, contextual reasoning), temporal action localization/ scene segmentation, and computational aesthetics or visual quality assessment. - Technical Leadership: Experience leading engineers through complex technical challenges, for example as a technical lead on a project or workstream. - Community Engagement: Experience presenting or mentoring within research communities, such as workshop talks, internal tech shares, or open-source maintainership. Check out Life at Huawei Ireland Research Centre: https://www.youtube.com/watch?v=3gR64sYSnOA&feature=youtu.be ### Due To The High Volume Of REPLIES, ### Only Candidates Who Are Shortlisted For Interview Will Be CONTACTED. Privacy Statement Please read and understand our West European Recruitment Privacy Notice before submitting your personal data to Huawei so that you fully understand how we process and manage your personal data received. http://career.huawei.com/reccampportal/portal/hrd/weu_rec_all.html …

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