2026 - Senior AI/ML Engineer – Multimodal Content Intelligence - Contractor

Location: Dublin, Ireland About Huawei Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. With integrated solutions across four key domains – telecom networks, IT, smart devices, and cloud services – we are committed to bringing digital to every person, home and organization for a fully connected, intelligent world. At Huawei, innovation focuses on customer needs. We invest heavily in basic research, concentrating on technological breakthroughs that drive the world forward. We have more than 180,000 employees, and we operate in more than 170 countries and regions. About the IRC Huawei Ireland Research Centre's (IRC) mission is to position Huawei as a recognized technology leader and global information and communications technology (ICT) solutions provider. We are building an industry-recognized multi-disciplinary Research Centre of experts focusing on medium-term to long-term issues to achieve this. The IRC will work closely with an open, innovative ecosystem with Huawei customers to address real-world issues. The IRC will also engage with key European universities to build a basic research capability to support Huawei technical projects. About The Role We are looking for a Senior Machine Learning Engineer to drive the development of our next-generation content intelligence systems. In this role, you will be a key technical contributor in developing complex multimodal understanding solutions across video, audio, image, and text. Leveraging cutting-edge Multimodal Large Language Models (MLLMs), you will build and optimize a self-evolving content analysis ecosystem. Your work will be instrumental in enhancing our core recommendation engine, directly impacting product performance and user engagement through advanced content signals. Key Responsibilities • Develop & Optimize Frameworks: Lead the implementation of multimodal frameworks focused on semantic understanding, narrative reasoning, and high-level content interpretation. • Technical Execution: Own the end-to-end development of high-performance systems that drive algorithmic innovation and resolve high-impact technical bottlenecks. • Collaboration & Integration: Work closely with cross-functional teams to integrate content signals into production recommendation and discovery pipelines. • Scalability & Performance: Ensure models are not only accurate but also optimized for low-latency inference and high-concurrency production environments. Requirements • Education: Master’s or PhD in Computer Science, AI, Machine Learning, or a related quantitative field. • Experience: 5–8+ years of professional experience in AI/ML research or advanced engineering (industry experience preferred). • Technical Depth: Strong hands-on experience in at least two of the following: 1. Multimodal Learning: Integration of video, text, image, and audio signals. 2. Computer Vision: Video understanding, temporal modeling, or representation learning. 3. NLP: Semantic modeling, content quality assessment, or news stream analysis. • Frameworks: Expert proficiency in PyTorch, TensorFlow, or JAX. • MLLM/VLM Expertise: Practical experience working with or fine-tuning Multimodal Large Language Models. • Production Skills: Proven track record of deploying large-scale AI models in production environments. Preferred Qualifications • Track Record: Contributions to high-impact projects or publications in top-tier conferences (e.g., CVPR, ICCV, NeurIPS). • System Design: Experience building automated content tagging or recommendation signals from the ground up. • Domain Knowledge: Familiarity with Digital Signal Processing for audio or aesthetic evaluation for images/video. Check out Life at Huawei Ireland Research Centre: DUE TO THE HIGH VOLUME OF REPLIES, ONLY CANDIDATES WHO ARE SHORTLISTED FOR INTERVIEWS 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.