Build 3D human pose models at Mecka AI using deep learning and articulated tracking to advance embodied AI research. Work model details are not specified.

This Research Scientist role focuses on proprietary foundation models for 3D human body tracking and articulated pose estimation. You will develop networks from scratch, model human-scene interaction, and address complex perception challenges for robotics systems. The work spans multi-view learning, temporal modeling, and physical interaction.

Key Responsibilities:
Design and train 3D pose estimation networks from scratch
Develop dense full-body mesh recovery and kinematic tracking
Scale architectures across multi-GPU clusters and multimodal datasets
Model occlusion, motion blur,



and multi-person interactions
Connect tracking outputs with contact and locomotion pipelines

Requirements:
Deep expertise in deep learning and 3D computer vision
Experience training large-scale vision models from scratch
Understanding of SMPL, inverse kinematics, and mesh estimation
Mastery of PyTorch and scaling frameworks
Experience curating massive image and video datasets

Apply 3D computer vision, articulated tracking, and model training expertise to Mecka AI’s embodied AI research.

📌 Research Scientist 3d Human Pose Richmond Hill
🏢 mecka
📍 Richmond Hill