Senior Staff Machine Learning Scientist, Assets

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.
• 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
• 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