Machine Learning Engineer

Machine Learning EngineerDigital Intelligence Foundations | Riyadh, Saudi Arabia | Full-time | On-siteAbout the RoleDigital Intelligence Foundations is looking for a Machine Learning Engineer to develop, optimize, and deploy machine learning solutions for real-world AI applications.The ideal candidate will have strong Python and machine learning skills, practical experience with model development, and an interest in applying modern AI technologies to business and enterprise solutions.ResponsibilitiesDevelop, train, and evaluate machine learning models.Prepare, clean, and analyze datasets.Optimize model performance and accuracy.Build and maintain machine learning pipelines.Integrate ML models into applications and APIs.Conduct experiments and evaluate different ML approaches.Collaborate with AI, software, and data teams.Deploy and monitor machine learning solutions.Document models, experiments, and technical processes.Use AI-assisted development tools to improve engineering productivity.Stay updated with modern machine learning and AI technologies.QualificationsBachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.2+ years of experience in Machine Learning or a related field.Strong proficiency in Python.Experience with PyTorch, Scikit-learn, or similar ML frameworks.Good understanding of machine learning algorithms and model evaluation.Experience with data preprocessing and feature engineering.Understanding of REST APIs, Git, and software development practices.Experience with Generative AI, LLMs, or Computer Vision is a plus.Practical experience using AI development tools such as ChatGPT, Claude, Gemini, or GitHub Copilot.Strong analytical and problem-solving skills.Good communication skills in Arabic and English.Preferred SkillsPython · PyTorch · Scikit-learn · Pandas · NumPy · SQL · Machine Learning · Deep Learning · Generative AI · LLMs · Computer Vision · REST APIs · Git · DockerJob DetailsJob Title: Machine Learning Engineer Location: Riyadh, Saudi Arabia Employment Type: Full-time Work Arrangement: On-site Experience: 2+ years