Machine Learning Engineer

Machine Learning Engineer

Key Responsibilities:

• Design, develop, and deploy machine learning models to solve real-world problems.
• Collaborate with data scientists, software engineers, and product teams to integrate ML models into production systems.
• Perform data preprocessing, feature engineering, and model evaluation.
• Optimize algorithms for performance and scalability.
• Conduct research on the latest machine learning techniques and tools.
• Monitor and maintain deployed models, ensuring accuracy and reliability.
• Document processes, models, and results for internal teams and stakeholders.

Required Skills and Experience:

• Strong proficiency in Python and machine learning libraries such as TensorFlow, PyTorch, scikit-learn, or similar.
• Experience with data processing tools like Pandas, NumPy, and SQL.
• Solid understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning).
• Experience with model deployment using cloud platforms (AWS, GCP, Azure) or containerization tools (Docker, Kubernetes).
• Familiarity with data visualization and reporting tools.
• Knowledge of statistics, probability, and data analysis techniques.
• Strong problem-solving skills and ability to work with complex datasets.