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Lead Machine Learning Engineer
3 months ago
Our client, a cutting-edge deep-tech AI platform in the MENA region, is looking for a Lead Computer Vision Engineer. They are looking for a Senior/Lead ML Engineer to help automate map creation using data science techniques.
The successful candidate would have a deep understanding of computer vision, machine learning, and geospatial data processing.
You will be responsible for
- Solving object detection, positioning, instance segmentation, and tracking.
- Development of algorithms and models to extract different features from videos captured by mobile mapping equipment and satellite data.
- Deployment of computer vision algorithms and ML models.
- Work closely with a cross-functional team of data scientists, software engineers, and product managers to define project requirements and deliver solutions.
- Mentor junior engineers and provide technical leadership in computer vision and machine learning projects.
- Conduct performance analysis and fine-tune models for optimal performance.
- Stay up-to-date with the latest advancements in machine learning and computer vision technologies.
The Must-Haves
- Minimum of 4 years of experience in computer vision and machine learning.
- Experience with image processing algorithms, including advanced computer vision techniques such as projective geometry, camera localization, motion estimation, and 3D reconstruction.
- Robust knowledge and practical experience in designing, training, evaluating, and optimizing Deep Learning networks.
- Strong proficiency in programming languages such as Python and C++ and experience with computer vision libraries (e.g., OpenCV, TensorFlow, PyTorch).
- Understanding of machine learning methods for classification, regression, and clustering.
- A highly driven individual who consistently stays informed about the latest developments and advancements in computer vision and deep learning methodologies and architectures.
The Nice-to-Haves
- Experienced with camera localization and motion estimation using a combination of different sensors.
- Experience with cloud computing platforms (e.g., AWS, Google Cloud) for large-scale data processing.
