Multimodal Generative AI Researcher

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About this role

Multimodal Generative AI Researcher Remote Multimodal Generative AI Researcher Location: Remote About the Role We're looking for a Research Scientist with deep expertise in training and fine-tuning large Vision-Language and Language Models (VLMs / LLMs) for downstream multimodal tasks. You'll help push the next frontier of models that reason across vision, language, and 3D , bridging research breakthroughs with scalable engineering. What You'll Do - Design and fine-tune large-scale VLMs / LLMs - and hybrid architectures - for tasks such as visual reasoning, retrieval, 3D understanding, and embodied interaction. - Build robust, efficient training and evaluation pipelines (data curation, distributed training, mixed precision, scalable fine-tuning). - Conduct in-depth analysis of model performance: ablations, bias / robustness checks, and generalisation studies. - Collaborate across research, engineering, and 3D / graphics teams to bring models from prototype to production. - Publish impactful research and help establish best practices for multimodal model adaptation. What You Bring - PhD (or equivalent experience) in Machine Learning, Computer Vision, NLP, Robotics, or Computer Graphics. - Proven track record in fine-tuning or training large-scale VLMs / LLMs for real-world downstream tasks. - Strong engineering mindset - you can design, debug, and scale training systems end-to-end. - Deep understanding of multimodal alignment and representation learning (vision-language fusion, CLIP-style pre-training, retrieval-augmented generation). - Familiarity with recent trends, including video-language and long-context VLMs , spatio-temporal grounding , agentic multimodal reasoning , and Mixture-of-Experts (MoE) fine-tuning. - Awareness of 3D-aware multimodal models - using NeRFs, Gaussian splatting, or differentiable renderers for

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