Hiring: Research Scientist – Computer Vision (Body Pose Detection) Company: Mecka Location: New York, United States Job Posted Time: 2026-09-17 02:22:27 Target Skills & Keywords : Agile, Computer Vision, Deep Learning, Fine-tuning, PyTorch, R About the job Required Skills: •To achieve this, we can provide a massive, continuous stream of high-quality, proprietary ground-truth human motion data captured by our infrastructure. You will use this data advantage to train networks that surpass current public baselines, owning the complete human-scene perception loop for our data engine. •Zero-to-One Model Development: Design, implement, and train state-of-the-art networks for 3D human pose estimation, dense full-body mesh recovery, and kinematic tracking. •Large-Scale Distributed Training: Scale multi-view and temporal ML architectures across multi-GPU clusters to handle massive, multi-modal datasets of humans navigating and interacting with their environments. •Loss & Architecture Innovation: Push the boundaries of current paradigms by developing novel loss functions that enforce biomechanical constraints, temporal smoothness, postural balance, and physical plausibility. •Human-Scene Interaction (HSI) & Complex Motion Modeling •Dynamic Scene Understanding: Build and train custom architectures capable of handling extreme motion blur, severe self-occlusion, and multi-person crowding inherent in real-world human behavior. •Allocentric & Egocentric Tracking: Use your models to track human bodies through complex spaces, mapping foot-to-ground contact, joint torques, and environmental affordances to provide rich regularization for downstream action-conditioned robotics models (especially humanoid robots). •Rapid Prototyping: Tackle novel, unmapped AI challenges as they arise. You will rapidly prototype and deploy new models for tasks spanning fine-grained action segmentation, intent prediction, and novel hardware sensor integrations. Qualifications: •Deep expertise in Deep Learning, 3D Computer Vision, and specifically Articulated Tracking / Human Body Pose Estimation. •Proven experience training large-scale vision models from scratch, not just running inference or fine-tuning existing checkpoints. •Strong theoretical and practical understanding of parametric human body models (e.g., SMPL, SMPL-X, GHUM, MHR, SOMA-X), inverse kinematics, and dense mesh estimation. •Mastery of PyTorch and deep learning scaling frameworks. •Comfortable operating in a fast-paced environment where priorities can shift rapidly to capitalize on new research or hardware capabilities. •Research Scientist positions require hyper-specific expertise. Please limit your applications to one research role. Applying to multiple Research Scientist positions suggests a lack of focus and may result in the rejection of all submissions. You may, however, apply to other non-research roles alongside your research application. •First-author publications in top-tier venues (CVPR, ICCV, ECCV, NeurIPS) focusing on 3D human pose tracking, human-scene interaction (HSI), human motion capture, or human mesh recovery. •Specific experience working with massive human motion and interaction datasets (e.g., AMASS, Human3.6M, EgoBody, PROX) and solving the unique optimization challenges they present. •The Data Advantage: You will have access to a scale and quality of proprietary spatial and temporal ground truth for human motion that most academic researchers only dream of. •Pure R&D & Model Ownership: You are not maintaining legacy systems; you are given a blank slate and the compute resources to build the state-of-the-art. Compensation: •$150,000 - $200,000 / year Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!