About the Role
MotionAnalytics is seeking a Senior Computer Vision Engineer with over 5 years of experience and expertise in computer vision to join our core team. We are revolutionizing biometric identification by emphasizing biomechanical signatures over facial recognition.
The Challenge
At MotionAnalytics, we are developing the world’s first foundational model for human motion. Your role is to bridge the gap between Computer Vision and Temporal Signal Processing, converting our core IP into production-ready algorithms. You will derive accurate biomechanical insights from noisy, real-world video to generate unique, unforgeable IDs. This position demands a rare combination of advanced algorithmic research and efficient production-level optimization.
What You’ll Do:
- Design and train state-of-the-art models for Gait Analysis, Pose Estimation, and Action Recognition.
- Push the boundaries of sequence modeling by developing next-generation architectures like Spatiotemporal Transformers and Graph Convolutional Networks to decode complex human kinematics.
- Establish system-level validation standards and lead data strategies for intricate model chains.
- Tackle real-world computer vision challenges such as extreme camera angles, low resolution, and occlusion.
- Own the full process: collaborate with engineering teams to transition models from Python research prototypes to high-performance, production-ready deployments.
Requirements
Academic Background: M.Sc. or Ph.D. in Computer Science, Electrical Engineering, Physics, or a related field.
Deep Research Expertise: Demonstrated experience in applied research utilizing contemporary AI techniques such as Large Multimodal Models (LMM), Sequential Modeling, Vision Transformers (ViT), and Re-Identification (Re-Id) systems for sophisticated computer vision tasks.
Experience: Over 5 years as a Data Scientist or Machine Learning Engineer, preferably with a background in Defense, High-Level-Security (HLS), or Biometrics.
Model Diagnostic Skills: Proficiency in regression testing, analyzing model behaviors, identifying root causes, and converting insights into practical enhancements.
Technical Skills: Advanced proficiency in Python and deep expertise in PyTorch (preferred) or TensorFlow, with substantial hands-on experience in processing video, images, or time-series data.
Nice to Have:
The "Bio" Factor: Expertise in Kinematics and Biomechanics.
Human-Centric Computer Vision: 3D pose estimation, human mesh recovery, and action recognition.
Deployment: Demonstrated experience in optimizing performance and model quantization for edge devices and cloud environments.
About the Company
MotionAnalytics develops MotionID, a breakthrough biomechanical AI that identifies people by how they move, not by their faces, clothing, or devices.
Based on over two decades of biomechanics research at Ben-Gurion University, MotionID transforms standard video into unique biomechanical signatures that enable reliable, hardware-free identification of the same individual across different videos. The technology performs in real-world conditions where traditional biometrics struggle, including when faces are covered, lighting is poor, and cameras are thermal, distant, ground-based, or aerial.
Join us in developing the world’s first large biomechanical foundation model. We are looking for a hands-on engineer skilled in designing mission-critical, engineering-grade systems that enable real-time operation of computer vision models.