Computer Vision Engineer Detection & Pose / Movement Analysis

What You'll Do

• Design and develop real-time computer vision pipelines for person and object detection.


• Build pose estimation and movement analysis models to interpret posture, gestures, and motion.


• Develop multi-object tracking systems with identity persistence across video frames.


• Optimize AI models for low-latency inference on edge and near-edge devices.


• Ensure reliable performance across varying lighting conditions, camera angles, and occlusions.


• Integrate vision models with live video streaming and processing frameworks.


• Evaluate and benchmark models using real-world datasets and live video feeds.


• Collaborate with cross-functional teams to deliver scalable AI solutions.


• Continuously improve detection accuracy, tracking stability, and inference performance.

Required SkillsComputer Vision & Deep Learning

• Object Detection: YOLO, Faster R-CNN, SSD


• Pose Estimation: OpenPose, HRNet, MediaPipe


• Multi-Object Tracking: DeepSORT, ByteTrack, OC-SORT

Programming & Frameworks

• Python


• PyTorch or TensorFlow


• OpenCV


• GStreamer / FFmpeg

Additional Expertise

• Image Processing & Feature Extraction


• GPU Acceleration & Performance Optimization


• TensorRT, ONNX, Quantization


• Real-time Video Processing


• Model Evaluation (Precision, Recall, Tracking Accuracy, Latency)

Experience Required

• 5+ years of hands-on experience in Computer Vision or Applied AI.


• Experience deploying real-time vision systems in production.


• Strong exposure to live video feeds, real-world datasets, and challenging deployment environments.

What You'll Build

You'll contribute to next-generation AI-powered vision systems capable of:

• Real-time human detection and tracking


• Pose and movement analysis


• Behavioral analytics


• Intelligent video understanding


• Scalable AI solutions for real-world applications