Mecka
Mecka

Mecka Physical AI के लिए बुनियादी ढाँचा तैयार करती है और रोबोटिक्स तथा embodied-AI टीमों को वास्तविक दुनिया में मानव गतिविधियों को ऐसे सिस्टम में बदलने में मदद करती है जो सीख सकें, जिनका मूल्यांकन किया जा सके और जो प्रयोगशाला के बाहर भरोसेमंद ढंग से काम कर सकें। इसका Egoverse प्लेटफ़ॉर्म बड़े पैमाने के egocentric डेटासेट्स को दृष्टि, गहराई, स्पर्श-संवेदन, गति और स्थानीयकरण से जुड़े टेलीमेट्री डेटा के साथ जोड़ता है।

डेवलपर टूल्स, APIs और एंटरप्राइज़ सेवाओं के माध्यम से Mecka कार्य-विशिष्ट रोबोटिक सिस्टम्स के मूल्यांकन और तैनाती में सहायता करती है। कंपनी हार्डवेयर OEMs, मॉडल डेवलपर्स और वाणिज्यिक साझेदारों के साथ काम करती है तथा स्वयं रोबोट बनाए बिना रोबोटिक्स के लिए डेटा और संचालन संबंधी परत उपलब्ध कराती है।

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.

विवरण

  • 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.

आवश्यकताएँ

  • 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.

लाभ

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

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