Computer Vision Engineer, 3D

The role

You will own the classical side of the stack, including traditional computer vision, temporal filtering, and inverse kinematics. You will work on the 3D hands pipeline to turn model predictions into clean, calibrated spatial data.

What you will do

• Own classical 3D geometry including multi-view geometry, triangulation, PnP, camera calibration, undistortion, and reprojection.
• Design and tune temporal filters like low-pass, Kalman-family, and interpolation.
• Run inverse kinematics and enforce physical constraints such as bone-length rigidity.
• Build checks to keep bad frames out of delivery.
• Turn model output into clean delivered data, reports, and QA metrics.
• Keep the pipeline running at scale.
• Build visualizers and dashboards to inspect trajectories, overlays, and failure cases.
• Act as the go-to engineer for classical computer-vision problems across the pipeline.

Required qualifications

• 5+ years of professional experience in software engineering and computer vision.
• Strong software engineering with clean, efficient, production Python.
• Solid multi-view geometry: triangulation, PnP, camera calibration, reprojection, and coordinate transforms.
• Temporal filtering and signal processing: low-pass and Kalman-family filters, interpolation.
• Inverse kinematics and rigid-body or bone-length constraints on articulated structures.
• Knowledge of ML to work with deep models such as pose and mesh regressors.
• A data-quality mindset comfortable with noisy real-world data and building QA.

Nice to have

• Human pose or mesh reconstruction (hand or body), including keypoint and mesh pipelines.
• Depth in Bayesian filtering or state estimation; experience with optimization frameworks such as Ceres or GTSAM.
• Building CV tooling such as trajectory visualizers and overlay or QA dashboards.
• Stereo, multi-view, or ego-exo capture experience.
• Light temporal ML, such as small networks for smoothing or gap-filling.
• C++

About the company

Mecka AI is building the data infrastructure layer for robotics and embodied AI. They design and operate global systems for data capture, data labeling, and hardware-enabled workflows for AI labs and robotics companies.