Machine Learning Engineer - Computer Vision

About the Role Our client, a dynamic force in the AI & Emerging Technologies landscape, is seeking a skilled Machine Learning Engineer with a specialization in Computer Vision. This role is based in Upington, Northern Cape, ZA , and offers a hybrid working arrangement, blending the benefits of in-office collaboration with the flexibility of remote work. You will be at the forefront of developing and deploying advanced computer vision models that power innovative solutions.

This position requires a deep understanding of machine learning principles, robust programming skills, and a passion for solving complex visual recognition and analysis challenges. You will work within a talented team, contributing to projects that push the boundaries of what's possible with AI and visual data. We are looking for an individual who is eager to learn, grow, and make a significant impact.

• Design, develop, train, and deploy machine learning models for computer vision tasks (e.g., image classification, object detection, segmentation).
• Implement and optimize deep learning architectures for computer vision applications.
• Process and analyze large image and video datasets.
• Collaborate with software engineers to integrate ML models into production systems.
• Conduct research into new computer vision techniques and algorithms.
• Evaluate model performance and iterate on improvements.
• Stay up-to-date with the latest research and industry trends in computer vision and ML.
• Document code, models, and experiments thoroughly.
• Participate in code reviews and contribute to team best practices.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• Proven experience in developing and deploying computer vision models.
• Proficiency in Python and ML libraries like Tensor Flow, PyTorch, or Keras.
• Strong understanding of deep learning concepts and architectures (CNNs, Transformers).
• Experience with image processing libraries (e.g., OpenCV).
• Familiarity with data augmentation techniques and handling large datasets.
• Excellent problem-solving and analytical skills.
• Ability to work effectively both independently and as part of a team in a hybrid environment.
• Good communication skills to articulate technical concepts.

• Competitive salary and performance incentives.
• Hybrid work model offering flexibility.
• Opportunity to work on cutting-edge AI projects.
• Professional development and training opportunities.
• Health and wellness benefits.
• Collaborative team environment.
• Contribution to innovative technology solutions.