Tech Lead, Computer Vision

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profile Job Location:

San Francisco, CA - USA

profile Monthly Salary: Not Disclosed
Posted on: 30+ days ago
Vacancies: 1 Vacancy

Department:

Engineering

Job Summary

Description



As a Tech Lead for the Applied Computer Vision Algorithms Team youll help drive our Reconstruct Understand and Localization capabilities. the greater team will be responsible for creating the high-fidelity visual and semantic mapsspecifically textured semantic meshes and Gaussian Splats as well as localization maps that allow our Large Geospatial Model (LGM) to perceive the world with human-like precision. Closely working with the R&D and product teams your work will bridge the gap between cutting-edge theory and real-world utility turning complex geospatial data into a persistent sense of space for the next generation of AI and robotics.


Requirements

  • Years of Experience:8 years of professional experience in Computer Vision Machine Learning or a related field (or 6 years with a PhD in a relevant domain).

  • Education:Bachelors degree in Computer Science Engineering or a related technical field; Masters or PhD preferred.

  • Core Technical Skills:Strong proficiency in C/C and Python for production-level software development.

  • Specialized Expertise:Proven experience in 3D Computer Vision/ML specifically with Structure from Motion (SfM) 3D reconstruction and Gaussian Splatting rendering techniques.

  • Hardware Optimization:Demonstrated ability to optimize algorithms for GPUs in Android or Linux environments.

  • Graphics Knowledge:Experience with computer graphics and C shader-based implementations.

  • Technical Leadership Experience:Previous experience tech leading a team of computer vision engineers in a high-growth environment.



Required Experience:

Staff IC

DescriptionAs a Tech Lead for the Applied Computer Vision Algorithms Team youll help drive our Reconstruct Understand and Localization capabilities. the greater team will be responsible for creating the high-fidelity visual and semantic mapsspecifically textured semantic meshes and Gaussian Splats a...
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