Array Labs
Staff Software Engineer - Computer Vision
$150K–$300K
Redwood City, CA · Hybrid · Staff · Full-time · Posted May 19, 2026
- Experience
- 5+ years of software engineering experience, with a substantial portion focused on computer vision.
- Visa sponsorship
- To conform to ITAR requirements, candidates must be U.S. citizens, lawful permanent residents of the U.S., protected individuals as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain required authorizations from the U.S. Department of State.
About the job
Develop and productionize computer vision software for Array’s photogrammetry and radar reconstruction pipelines and related 3D geospatial data systems.
What you'll do
- Improve pipeline stages such as bundle adjustment, dense matching, point cloud generation, geometric refinement, and geo-referencing.
- Develop and optimize database schemas and storage for large-scale 3D geospatial data.
- Contribute to data infrastructure, analytics, and systems that deliver satellite data to customers.
What they ask for
- 5+ years of software engineering experience, with a substantial portion focused on computer vision.
- Strong proficiency in Python and C++; experience with cloud platforms and containerization technologies.
- Strong foundation in geometric computer vision, including camera modeling, epipolar geometry, and multi-view reconstruction pipelines.
- Excellent communication skills and ability to make high-quality technical decisions in a startup environment.
Nice to have
- Experience with geospatial concepts, remote sensing, or robotics/autonomous vehicle sensor data; familiarity with digital signal processing, radar algorithms, or SAR concepts.
- Familiarity with deep learning approaches to 3D vision, performance optimization with C++ or CUDA, or visualization tools such as Cesium or Three.js.
Pay
USD 150,000–300,000 per-year-salary (base salary)
Tools
Python, C++, AWS, GCP, Azure, Docker, Kubernetes, CUDA
AI focus
The role may involve deep learning approaches to 3D vision, including NeRF, 3D Gaussian Splatting, learned feature matching, or depth estimation.
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