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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. Solid exposure to live video feeds, real-world datasets, and challenging deployment settings. 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 .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.