Research Scientist – VLM Generalist

Full Time

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Stability AI

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 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 / Preferred

  • Experience 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.