Technical Lead
US$256,500 – US$315,000 / yr base salary
Posted 18 Sep 2026
Advertised as “Technical Lead, Computer Vision”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 8+ yrs
- Management level
- People management
- Employment
- Hybrid
- Contract
- Full-time
| Base salary | US$256,500 – US$315,000 / yr |
|---|
Field of studyComputer Science, Engineering (or related)
Study levelBachelor's
Study levelMaster's or higher
At Niantic Spatial, we’re building the future of geospatial AI. Powered by a proprietary database of over 30 billion posed images and a groundbreaking third-generation digital map, our mission is to develop spatial intelligence that helps both humans and machines better understand, navigate, and engage with the physical world. Our high-fidelity mapping technology unlocks a new dimension of interaction—laying the foundation for AI to truly comprehend and operate within real-world environments. Join us as we build a living model of the world that people and machines can talk to.
As a Tech Lead for the Applied Computer Vision Algorithms Team, you’ll help drive our “Reconstruct”, “Understand” and “Localization” capabilities. This team is responsible for creating the high-fidelity visual and semantic maps—specifically 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.
Job Responsibilities
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Applied Research & Implementation: Actively translate top-tier research papers (e.g., from CVPR, ECCV, NeurIPS) into production-grade features within our tech stack.
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Technical Leadership: Lead the design and implementation of 3D reconstruction pipelines, focusing on Structure from Motion (SfM) and high-fidelity mesh generation as well as 3D gaussian splats.
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Algorithm Optimization: Develop and optimize Gaussian Splatting quality algorithms and general ML code for high-performance execution on CPU and GPU.
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Production Implementation: Write and maintain high-performance, shader-based production code in C++ for Android and Linux environments.
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Technical Strategy & Mentorship: Work with engineering leadership to define the technical roadmap and quarterly objectives for the Applied CV Team; provide high-level mentorship and code governance to elevate the team’s technical bar.
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Cross-Functional Collaboration: Partner with the Research and Spatial Solutions teams to turn strategic goals into actionable plans.
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Quality & Benchmarking: Drive decision-making creating high quality data that allows the accurate spatial grounding of AI queries with structural, semantic and location specific knowledge.