ML Engineer

• Design, develop, and deploy machine learning and deep learning systems for scalable applications.

• Implement appropriate ML algorithms based on business and technical requirements.

• Conduct machine learning experiments, model training, validation, and performance tuning.

• Work extensively with Python and ML libraries such as Scikit-learn, TensorFlow, PyTorch, OpenCV, and NumPy.

• Build self-learning systems that continuously improve using data-driven approaches.

• Apply statistical and data science principles to solve complex business problems.

• Collaborate with data engineers and software teams to integrate ML models into production systems.

• Stay updated with latest advancements in AI, ML, and deep learning technologies.

• Optimize models for accuracy, scalability, and performance in production environments.

• Analyze large datasets to extract meaningful insights and patterns.