About the role
AI Research Scientist – Careers – QuiverAI Skip to main content $8.3M seed led by a16z Announcing our $8.3M seed funding round led by a16z | Read the blog post Solutions Developers Enterprise Pricing Company Careers Blog Get started Sign in Get started Careers / Research AI Research Scientist Research · Full-time · Hybrid (San Francisco) Apply for this role About QuiverAI QuiverAI is building the future of AI-powered design tools. We help designers and teams create stunning vector graphics, illustrations, and brand assets with the power of generative AI. Our mission is to democratize great design by making professional-quality creative tools accessible to everyone.
About
the Role QuiverAI helps creative teams move from idea to output faster. We are looking for an AI Research Scientist who can push forward foundational models for visual code generation and help turn strong research into shipped capabilities. You will work on problems that matter alongside leading researchers, push the frontier, publish and present at conferences, and turn ideas into real impact. This is a hybrid role based in San Francisco. What You Will Do Design, train, and evaluate large language and vision models across pre-training, mid-training, and reinforcement learning stages. Own experiments end-to-end across hypotheses, datasets, metrics, and results. Develop new architectures and training approaches for visual code generation. Implement and extend state-of-the-art techniques in vision-language models, diffusion models, transformers, and generative AI. Work closely with product and engineering teams to turn research into production-ready capabilities. Publish and present research at top-tier venues and help shape our research culture. What We’re Looking For PhD in Computer Science, Machine Learning, or a related field, or equivalent industry research experience. Strong publication record in machine learning, NLP, and/or computer vision. Deep expertise in PyTorch and modern deep learning tooling. Experience with generative models, especially vision-language models, reinforcement learning, diffusion, and transformer architectures. Familiarity with modern LLM training paradigms, including multi-turn or agentic setups, is a plus. Excellent communication and ability to work cross-functionally. Experience with visual code generation, vector graphics, or SVG is a plus. Contributions to open-source ML projects are a plus. What We Offer Competitive