Senior Staff Machine Learning Scientist, Assets

Webflow is the agentic web marketing platform for modern marketing teams, helping organizations build, manage, and optimize high-performing web experiences that drive predictable growth and strengthen brand trust. Building at Webflow will need grit, because we move fast, without ever sacrificing craft or quality. We’re looking for a Senior Staff Machine Learning Scientist to help us solve challenging problems to address emerging customer needs and behaviors. The ideal candidate can move fast but with high quality, and views the early stages of product development as a creative canvas and opportunity for high impact. About the role: Location: Remote-first (United States; BC & ON, Canada) Full-time Permanent Exempt Our cash compensation amount for this role ranges depending on the cost of labor of the geographic area. The ranges shared below may change if you are hired in another geographic location. United States (all figures cited below in USD and pertain to workers in the United States) Zone A: 232,000 - 290,000 Zone B: 217,600 - 272,000 Zone C: 204,800 - 256,000 Canada (All figures cited below in CAD and pertain to workers in ON & BC, Canada) 253,000 - 316,000 Please visit our Careers page for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter. Application Information: Application deadline: applications accepted on an ongoing basis until position is closed and filled This posting is for a new position Reporting to the Director, Engineering As a Senior Staff Machine Learning Scientist, you’ll: Lead and drive ambitious research initiatives that advance the state of the art in computer vision, multimodal understanding, and visual generation. Develop novel models, algorithms, and training methodologies for challenging vision problems such as image understanding, video understanding, visual search, scene representation, segmentation, detection, generation, and multimodal reasoning. Translate cutting-edge research into practical model improvements that can shape product direction and unlock new user experiences. Design, implement, train, and optimize large-scale vision and multimodal foundation models across diverse datasets and tasks. Partner closely with applied scientists, ML engineers, and product teams to move research from exploration to production-ready systems. Set technical direction for high-impact research areas, identifying promising bets and influencing longer-term strategy for vision and multimodal AI. Mentor other scientists and engineers, raise the quality bar for research, and help build a strong scientific culture across the team. Stay at the forefront of research in computer vision, multimodal learning, generative modeling, and foundation models, and apply emerging techniques to real-world problems. About you: Requirements: BA/BS degree or equivalent experience You’ll thrive as a Senior Staff Machine Learning Scientist if you: Deep theoretical and practical expertise in computer vision, with strong foundations in areas such as representation learning, visual recognition, image or video generation, multimodal learning, and large-scale model training. Advanced degree in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or a related field; PhD strongly preferred. 8+ years of relevant industry and/or research experience, or equivalent impact, including a track record of driving major research initiatives in computer vision or multimodal machine learning. Strong experience with state-of-the-art vision and multimodal model architectures, including transformers, diffusion models, contrastive learning approaches, and foundation models. Proven ability to formulate research problems clearly, design rigorous experiments, and translate findings into meaningful model or product advances. Strong coding and prototyping skills in Python, with the ability to write clean, scalable, and well-documented research code. Proficiency in modern deep learning frameworks such as PyTorch and TensorFlow. Demonstrated technical leadership, including mentoring scientists or engineers and influencing research direction across a team or organization. Strong communication skills, with the ability to present complex research clearly to both technical and cross-functional audiences. Stay curious and open to growth — demonstrating a proactive embrace of AI, and actively building and applying fluency i