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Salary
$150k – $300k per year
Location
In office (Redwood City)
Seniority
Staff · 5+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 9, 2026. First seen by Alion on Sep 17, 2026.

Overview
Company
Impact
Profile match
Array Labs creates powerful, modular, and flexible radar systems designed for mass production — delivering greater capability and performance at a fraction of the cost of traditional approaches.

Join Array as a Staff Software Engineer specializing in Computer Vision. In this role, you will develop and deploy our 3D processing capabilities, including photogrammetry and radar reconstruction pipelines. You will work closely with scientists and engineers, improve accuracy and throughput, and contribute to broader software engineering efforts. Candidates should have a strong foundation in geometric computer vision, 5+ years of software engineering experience, and proficiency in Python and C++.

Missions

  • Develop and deploy Array's 3D processing capabilities, including photogrammetry and radar reconstruction pipelines.
  • Productionize and continuously improve Array's photogrammetry and radar image formation pipelines using industry best practices.
  • Contribute to broader software engineering efforts across the company, including data infrastructure, analytics, and systems to deliver satellite data to customers.

Profil recherché

- Strong foundation in geometric computer vision, spanning camera modeling, epipolar geometry, and multi-view reconstruction pipelines (stereo, SfM, MVS, bundle adjustment)

- Excellent communicator, with the ability to make high-quality technical decisions in a startup environment

- 5+ years of software engineering experience, with a substantial portion focused on computer vision

- Strong proficiency in Python and C++, experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (e.g. Docker, Kubernetes)

- Experience with geospatial concepts, remote sensing data, or robotics/autonomous vehicle sensor data

- Familiarity with digital signal processing, radar algorithms, or SAR concepts

- Familiarity with deep learning approaches to 3D vision (e.g. NeRF, 3D Gaussian Splatting, learned feature matching, or depth estimation)

- Experience with C++ or CUDA for performance optimization

- Ability to build visualization tools for geospatial or 3D data (Cesium, Three.js, or similar)

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