Posture Vision, an innovative app aimed at improving posture through real-time visual analysis. We are leveraging the latest advancements in computer vision and machine learning to deliver insights directly on devices. Role Overview We are looking for a skilled Machine Learning Engineer – Computer Vision with experience in mobile integration to develop, deploy, and optimize computer vision models on Android and iOS platforms. Your expertise will be critical in ensuring smooth and efficient performance for real-time posture detection. Responsibilities Develop and integrate computer vision models (e.g., pose detection, face tracking) for mobile platforms. Build and optimize real-time inference pipelines on mobile (TensorFlow Lite, Core ML, or ONNX). Collaborate with engineering team to ensure seamless integration and smooth user experience. Conduct experiments and deploy edge-optimized models for low-latency applications. Analyze large datasets to improve posture detection accuracy. Stay updated on the latest trends in computer vision, MLOps, and mobile optimization techniques. Qualifications Strong experience with mobile integration using TensorFlow Lite, Core ML, or ONNX. Expertise in Python, with knowledge of frameworks like TensorFlow, PyTorch, and OpenCV. Familiarity with Android Studio and Xcode for mobile development. Experience with pose estimation models such as MoveNet, BlazePose, or Posenet. Strong knowledge of edge computing, GPU acceleration, and model optimization. Familiarity with cloud-to-mobile inference pipelines. Preferred Skills Hands-on experience with real-time posture or fitness tracking applications. Knowledge of augmented reality (AR) for posture correction or related solutions. Familiarity with MLOps tools and processes for mobile deployment. Exposure to health tech applications and usability-focused mobile app design. Job Type: Full-time Schedule: 8 hour shift Monday to Friday Weekends as needed Work Location: Remote