Machine Learning Engineer

Key Responsibilities

• Design, develop, and implement machine learning and deep learning models and algorithms.
• Analyse large datasets to extract meaningful insights that inform AI model development.
• Train, validate, and fine-tune AI models to ensure robustness, accuracy, and performance.
• Develop prototypes and run experiments to benchmark different AI approaches.
• Collaborate with cross-functional teams including data engineers, software developers, and product managers.
• Deploy AI solutions into production environments and integrate with existing systems.
• Monitor AI system performance and make adjustments to improve outcomes.
• Document workflows, models, and algorithms and present findings to both technical and non-technical stakeholders.
• Stay updated with the latest advancements in AI and machine learning technologies.
• Troubleshoot and resolve issues related to AI systems and production models.
• Design, develop, and deploy ML models for production use.
• Preprocess, clean, and analyze large datasets.
• Implement model training, tuning, and evaluation pipelines.
• Collaborate with software engineers to integrate ML solutions into applications.
• Stay updated with the latest ML tools, frameworks, and techniques.
• 2-14 years of proven experience as a Machine Learning Engineer or Data Scientist.
• Strong knowledge of Python and ML frameworks (TensorFlow, PyTorch, Scikit-Learn).
• Experience with data preprocessing, feature engineering, and model optimization.
• Understanding of backend integration and APIs for ML deployment.
• Strong problem-solving and analytical skills.
• Prior experience in end-to-end ML projects (academic + professional).