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Mecka
Mecka
11 – 50 Employees
Artificial IntelligenceEnterpriseSaaS

Mecka builds infrastructure for Physical AI, helping robotics and embodied-AI teams turn real-world human activity into systems that can learn, be evaluated, and operate reliably outside the lab. Its Egoverse platform combines large-scale egocentric datasets with telemetry across vision, depth, tactile sensing, motion, and localization.

Through developer tools, APIs, and enterprise services, Mecka supports the evaluation and deployment of task-specific robotic systems. The company works with hardware OEMs, model developers, and commercial partners, providing the data and operational layer for robotics without manufacturing robots itself.

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3D Computer Vision Engineer at Mecka (Toronto Hybrid)

Lead 3D geometry, temporal filtering, and inverse kinematics for robotics and embodied AI. Help build reliable data infrastructure and quality checks for production systems.

CACanada
$200,000 – $230,000 / year
HybridFull-timeMiddleSeniorEnglish RequiredComputer Vision EngineerMachine Learning Engineer
C++Python

Description

  • Develop classical 3D geometry for multi-view reconstruction, triangulation, PnP, camera calibration, undistortion, and reprojection.
  • Tune temporal filters to reduce jitter while preserving genuine motion.
  • Apply inverse kinematics and physical constraints, including rigid bone lengths.
  • Create validation checks that keep faulty frames out of delivered data.
  • Turn model outputs into clean datasets, reports, and quality metrics.
  • Maintain a data pipeline that operates at scale.
  • Create visualizers and dashboards for trajectories, overlays, and failure analysis.
  • Provide classical computer vision expertise across the organization.
  • Work with research teams and interpret model behavior without training models.

Requirements

  • At least five years of professional experience in software engineering and computer vision.
  • Write clean, efficient Python for production; C++ experience is a plus.
  • Strong command of multi-view geometry, including triangulation, PnP, camera calibration, reprojection, and coordinate transforms.
  • Experience with temporal filtering and signal processing, including low-pass and Kalman-family filters and interpolation.
  • Knowledge of inverse kinematics and rigid-body or bone-length constraints for articulated structures.
  • Experience interpreting deep model outputs and failure modes, such as those from pose and mesh regressors; model training is not required.
  • Comfort working with noisy real-world data and building quality checks that catch issues before customers do.
  • Human pose or mesh reconstruction experience is a plus.
  • Bayesian filtering, state estimation, and optimization tools such as Ceres or GTSAM are a plus.
  • Experience creating computer vision tools such as trajectory visualizers and overlay or quality dashboards is a plus.
  • Stereo, multi-view, or ego-exo capture experience is a plus.
  • Experience with lightweight temporal machine learning is a plus.

Benefits

  • Equity.
  • Health and wellness benefits.
  • Additional company programs.

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