Ceres Solver Jobs in Computer Vision
Browse CV roles that require Ceres Solver across all industries and experience levels.
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What is Ceres Solver?
Ceres Solver is Google’s C++ library for modelling and solving large non-linear least-squares problems, with automatic differentiation, sparse solvers and robust loss functions. It is the standard optimiser for bundle adjustment, calibration and sensor fusion.
Where Ceres Solver is used
Bundle adjustment in reconstruction pipelines, camera and multi-sensor calibration, and the back ends of visual-inertial odometry and SLAM systems.
Roles that ask for Ceres Solver
- SLAM Engineer
- Calibration Engineer
- 3D Vision Engineer
- Sensor Fusion Engineer
- Optimisation Engineer
Related skills & tools
Ceres Solver jobs — common questions
What makes Ceres so widely used?
Automatic differentiation removes the need to hand-derive Jacobians, which eliminates a major source of subtle bugs. Combined with strong sparse solvers and clear documentation, it makes large geometric optimisation problems tractable.
What is a robust loss function and why does it matter here?
A cost function such as Huber or Cauchy that reduces the influence of large residuals, so a handful of bad feature matches cannot dominate the solution. Geometric vision data almost always contains outliers, making this essential.
Which systems use Ceres?
COLMAP for structure from motion, many visual-inertial odometry systems, and a large share of production calibration pipelines. Encountering it is close to inevitable in 3D vision work.