Computer Vision Leader

Computer Vision & Deep Learning Expertise:
Egocentric Vision & Hand Tracking: Deep expertise in hand pose estimation, object tracking, and egocentric action recognition (e.g., MediaPipe, HaMeR, Ego4D ecosystem). Must be able to detect hand presence, occlusion, and interaction with objects in the center of the frame.
Action Recognition & Semantic Understanding: Strong experience with video understanding models (e.g., SlowFast, TimeSformer, VideoCLIP) to verify if the actor's actions match the assigned tasks.
Image Quality Assessment (IQA): Proficiency in classical and deep-learning-based IQA methods to automatically detect over/underexposure, motion blur, and excessive camera shake.
Privacy & Anonymization: Proven ability to build robust detection pipelines for faces, demographics (children), and PII (ID cards, passports, logos) using models like RetinaFace, YOLO, and OCR (Tesseract/EasyOCR) for automatic blurring/redaction.
Video Processing & Sensor Fusion:
Advanced Video Processing: Mastery of FFmpeg, OpenCV, and GStreamer for programmatic video manipulation, trimming, metadata extraction (FPS, bitrates, compression), and batch validation.
Sensor Data Handling (IMU): Experience working with time-series data and sensor fusion, specifically synchronizing head-mounted IMU telemetry (accelerometer/gyro) with video frames.
Multimodal Processing (Bonus): Familiarity with audio processing and Speech-to-Text (e.g., Whisper) to validate spoken commands in video audio tracks.
Engineering & Deployment:
Programming: 5+ years of software engineering experience with strong proficiency in Python and C++.
Frameworks: Expert in PyTorch; familiar with model optimization and inference acceleration using TensorRT, ONNX, or OpenVINO.
Cloud & MLOps: Experience deploying high-throughput CV pipelines on AWS (EC2 GPU instances, SageMaker, or EKS) and working with large-scale storage (S3).