management, enhancing customer experiences, and ensuring regulatory compliance on a global scale. Key Responsibilities End-to-End Model Development: Lead the entire ML lifecyclefrom problem framing, data exploration, and featureengineering to model training, validation, deployment, and monitoring in production environments. Advanced Algorithm Design: Develop and implement sophisticated machine learning algorithms (e.g., Gradient Boosting, NLP, Deep Learning, Graph More ❯
months. Technical Skills Machine Learning & Deep Learning Supervised/unsupervised/reinforcement learning Model selection, training, validation, and evaluation Deep learning architectures (CNNs, RNNs, Transformers) Data Science Statistical analysis, featureengineering, A/B testing Experiment design and hypothesis testing MLOps & Engineering Scalable ML systems (batch and real-time) ML pipelines, CI/CD, monitoring, deployment Familiarity More ❯
models and solutions. The AI Engineer will:· Design and implement AI-powered solutions· Work with Python, SQL/NoSQL, and APIs for integration· Test AI applications· Improve performance through featureengineering· Explore and incorporate the latest open-source AI/ML tools into business solutions· Develop and deploy machine learning models · Solve business problems· Clearly communicate technical ideas … in API development/integrationAbility to analyze model performance In return our client offers outstanding benefits and a great working environment. Please apply for more opportunity on this AI Engineering position. More ❯
