Huawei Ireland Research Centre
2026 - Senior Machine Learning Engineer - Generative Vision & Video - Permanent
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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 world. At Huawei, we have two key drivers of innovation: science and technology, and customer needs. Both commercial value and market demands are driving our innovation and determining how we invest in science and technology. Breakthroughs in technology, in return, stimulate customer needs and allow us to create greater value for customers.
About the IRC
Huawei Ireland Research Centre's (IRC) mission is to position Huawei as a recognised technology leader and global information and communications technology (ICT) solutions provider. We are building an industry-recognised 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 Job
The Terminal Cloud Technology Lab is looking for a Senior Machine Learning Engineer to drive the development of our next-generation content intelligence systems, with a strong focus on generative vision and video. In this role, you will have the opportunities to explore areas such as image and video generation, controllable content editing, multimodal understanding, 3D-aware generation, and intelligent visual adaptation. You will work on research-driven problems with clear product relevance, turning promising machine learning techniques into practical prototypes and scalable solutions. The position is open to candidates with different levels of industry experience. Level and scope will be calibrated based on technical depth, research capability, and relevant experience.
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Responsibilities
- Research, implement, and evaluate state-of-the-art methods in generative vision, video generation, and multimodal AI
- Develop and prototype algorithms for image/video generation, editing, enhancement, and visual content adaptation
- Explore methods for improving controllability, temporal consistency, spatial consistency, structure preservation, and visual quality
- Investigate multimodal and structured conditioning approaches for more controllable and context-aware generation
- Design experiments, datasets, benchmarks, and evaluation methodologies to assess model quality and generalization
- Analyze model failure modes and propose improvements to model architecture, training strategy, data, and evaluation
- Adapt and fine-tune existing foundation models where appropriate, while exploring new modelling approaches when needed
- Collaborate with researchers, engineers, and product teams to translate research prototypes into usable systems
- Stay up to date with advances in generative AI, computer vision, computer graphics, and multimodal learning, and identify relevant technologies for practical applications
Basic Qualifications
- Education: Master's or PhD in Computer Science, AI, Machine Learning, Computer Vision, Computer Graphics, or a related field, or equivalent practical experience
- Hands-on experience in at least one relevant area, such as:
- image or video generation
- generative modelling
- image/video editing or enhancement
- multimodal learning
- 3D vision or visual computing
- Strong programming skills in Python
- Frameworks: Expert proficiency in PyTorch, TensorFlow, or JAX.
- 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.
- Demonstrated interest in generative AI and visual content technologies
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Preferred Qualifications
- Experience in one or more of the following areas:
- Video generation, image-to-video, video-to-video, video inpainting or outpainting
- Diffusion models, Diffusion Transformers (DiT), flow matching, or related generative architectures
- Temporal consistency, optical flow, correspondence, or video representation learning
- Depth estimation, 3D vision, neural rendering, or 3D-aware generation
- Layout understanding, visual composition, or structured visual generation
- Publications & Research Recognition: Contributions to high-impact projects or publications in top-tier conferences such as CVPR, ICCV, ECCV, SIGGRAPH, NeurIPS, or ICLR.
- 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
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