Machine Learning Engineer
1 week ago
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).
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