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Job Requirements - Deep Learning Model Development Design, train, and optimize CNN-based models for classification, object detection, and segmentation using TensorFlow/PyTorch - Computer Vision Algorithms Develop image processing algorithms using OpenCV for filtering, feature extraction, and measurement and Design and Implement proprietary Computer Vision algorithms - Camera Calibration & Vision Accuracy Develop Logics for Camera Calibration, Lens Distortion Correction, and coordinate mapping for accurate Vision Guidance Applications and Measurement Systems - Data Preparation & Annotation Prepare datasets, labeling, and augmentation for training deep learning models - Model Deployment Deploy trained models into production systems - Cross-functional Collaboration Collaborate with automation, hardware, and software teams for system integration - Documentation Document calibration process, models, datasets, and deployment workflows Work Experience - B.Tech / BE in Computer Science, Electronics, Mechatronics, or related field - Strong Proficiency in Python and C++ - To Build foundational methods for traditional Computer Vision Tools - Hands-on experience with TensorFlow and/or PyTorch in Developing Models, Optimization and Deployement - Robust understanding of Convolutional Neural Networks (CNNs), Experience with CNN architectures (ResNet, VGG, MobileNet, YOLO, SSD, Faster R-CNN) - Knowledge of object detection, image classification, and segmentation techniques - Strong experience with OpenCV and classical image processing and understading of fundamantals - Understanding in camera calibration techniques (intrinsic/extrinsic parameters, distortion correction) for Vision Guidance, coordinate transformation and Measurement Applications. - Knowledge of camera pipelines and real-time image acquisition using Gige Vision/GeniCam/USB3.0 Vision Protocols - Experience with Dataset Preparation, Annotation, and Augmentation Tecchniques - Familiarity with deploying models on edge devices or industrial systems - Knowledge of GPU acceleration (CUDA) is an added advantage - Strong debugging, optimization, and analytical problem-solving skills. - Understanding of Machine Vision Field - Vision Systems is added advantage. .
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.