Design, implement, and deploy scalable machine learning models and AI algorithms.Collaborate with cross-functional teams to define use cases, collect requirements, and deliver AI-driven solutions.Conduct data preprocessing, feature engineering, and exploratory data analysis.Train, test, and optimize models for performance, scalability, and accuracy.Monitor and maintain ML pipelines and deployed models in production.Stay updated with the latest research, tools, and best practices in AI/ML.Document experiments, workflows, and results clearly for future reference and reproducibility.Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics a related field.Solid understanding of machine learning algorithms (supervised, unsupervised, deep learning).Proficiency in Python and ML libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, XGBoost, or similar.Experience with data manipulation and analysis tools (Pandas, NumPy, SQL).Understanding of model evaluation metrics and techniques to improve model performance.Knowledge of cloud platforms (AWS, Azure, GCP) and MLOps is a plus.Strong problem-solving skills, analytical mindset, and ability to communicate technical concepts to non-technical stakeholders.Contributions to open-source AI/ML projects or publications in the field.
