Research Scientist – VLM Generalist at Stability AI

Research Scientist VLM GeneralistLocation: RemoteAbout the RoleWere 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. Youll help push the next frontier of models that reason across vision language and 3D bridging research breakthroughs with scalable engineering.What Youll DoDesign 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 BringPhD (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 (visionlanguage 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 grounded reasoning and 3D scene understanding.Hands-on experience with PyTorch / DeepSpeed / Ray and distributed or mixed-precision training.Excellent communication skills and a collaborative mindset.Bonus / PreferredExperience integrating 3D and graphics pipelines into training workflows (e.g. mesh or point-cloud encoding differentiable rendering 3D VLMs).Research or implementation experience with vision-language-action models world-model-style architectures or multimodal agents that perceive and act.Familiarity with efficient adaptation methods LoRA adapters QLoRA parameter-efficient finetuning and distillation for edge deployment.Knowledge of video and 4D generation trends latent diffusion / rectified flow methods or multimodal retrieval and reasoning pipelines.Background in GPU optimisation quantisation or model compression for real-time inference.Open-source or publication track record in top-tier ML / CV / NLP venues.Equal Employment Opportunity:We are an equal opportunity employer and do not discriminate on the basis of race religion national origin gender sexual orientation age veteran status disability or other legally protected statuses. Key Skills Laboratory Experience,Machine Learning,Python,AI,Bioinformatics,C/C++,R,Biochemistry,Research Experience,Natural Language Processing,Deep Learning,Molecular Biology Employment Type : Full Time Experience: years Vacancy: 1