Senior Staff Machine Learning Scientist, Assets
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WebflowComputer vision
Remote-first (United States; BC & ON, Canada)Full-TimeStaff
Salary232,000 - 290,000 USD per year
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Job Details
- Experience
- 8+ years of relevant industry and/or research experience, or equivalent impact
- Required Skills
- PythonPyTorchTensorflowComputer Vision
Requirements
- BA/BS degree or equivalent experience.
- 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.
- Track record of driving major research initiatives in computer vision or multimodal machine learning.
- Deep theoretical and practical expertise in computer vision, including representation learning, visual recognition, image or video generation, multimodal learning, and large-scale model training.
- Experience with transformers, diffusion models, contrastive learning approaches, and foundation models.
- Ability to formulate research problems, design rigorous experiments, and translate findings into model or product advances.
- Strong Python coding and prototyping skills, including clean, scalable, well-documented research code.
- Proficiency with PyTorch and TensorFlow.
- Technical leadership experience, including mentoring scientists or engineers and influencing research direction.
Responsibilities
- Lead research initiatives in computer vision, multimodal understanding, and visual generation.
- Develop models, algorithms, and training methods for image and video understanding, visual search, scene representation, segmentation, detection, generation, and multimodal reasoning.
- Translate research into practical model improvements that inform product direction and user experiences.
- Design, implement, train, and optimize large-scale vision and multimodal foundation models across datasets and tasks.
- Partner with applied scientists, ML engineers, and product teams to move research into production-ready systems.
- Set technical direction for research areas and influence longer-term vision and multimodal AI strategy.
- Mentor scientists and engineers and raise the quality of research.
- Track emerging research in computer vision, multimodal learning, generative modeling, and foundation models, and apply relevant techniques to real-world problems.
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