ML Engineer
Robert Walters

Our client, the technology arm of a UAE-based consulting group, is seeking an ML Engineer to join their team in Dubai, United Arab Emirates. They are focused on delivering unmatched tech solutions for industry leaders in the Mining & Precious Metals industry.
Role Summary
This role focuses on designing, implementing, and deploying machine learning and neural network models, with a strong emphasis on image processing, optical character recognition (OCR), and feature extraction. The ideal candidate will have hands-on experience in deploying deep learning solutions and a solid foundation in computer vision techniques.
Key Responsibilities
Perform feature extraction on images with varying levels of reflection, shadow, contrast, and exposure to maximize the utility of the image data.
Optimize existing models for improved performance and efficiency in real-world applications.
Design and implement lightweight, production-ready models for use cases including image forensics, ID classification, face liveness detection, and document verification.
Stay updated with the latest advancements in deep learning and computer vision, incorporating cutting-edge techniques into workflows.
Conduct robust testing and validation of models to ensure accuracy and reliability.
Apply data augmentation techniques to enrich training and validation datasets.
Deploy neural network models to cloud platforms such as AWS or GCP for integration with broader applications.
Set up reinforcement learning pipelines to enable automatic retraining of models at scheduled intervals.
Document processes, algorithms, and workflows in line with software development best practices.
Review academic research and implement proofs-of-concept to evaluate feasibility for applied use cases.
Apply knowledge of transformers and develop custom Retrieval-Augmented Generation (RAG) and LLM pipelines for tasks such as summarization, clustering, translation, and classification.
Qualifications
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field.
Minimum of 3 years of hands-on experience in designing and deploying neural network architectures.
At least 1 year of focused experience in image processing and feature extraction.
Proficient in deep learning platforms such as TensorFlow, PyTorch, and Keras, with a strong focus on their application in computer vision and convolutional neural networks (CNNs).
Strong programming skills in Python, coupled with solid understanding of software engineering principles and best practices.
Experienced in deploying neural networks on cloud platforms, ensuring seamless integration into various applications by team members.
Fast learner with an agile mindset and a continuous improvement approach to system design and implementation.
Preferred Skills
Hands-on experience with cloud services like AWS for training and deploying machine learning models.
Familiarity with MLOps practices and tools for managing the end-to-end machine learning lifecycle, including version control, monitoring, and automation.
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