Data engineer - Machine learning

As a Machine Learning Engineer, your role will involve working with Big Data, Neural network (deep learning), and reinforcement learning. Your key responsibilities will include: - Designing machine learning systems - Researching and implementing appropriate ML algorithms and tools - Developing machine learning applications based on requirements - Selecting suitable datasets and data representation methods - Running machine learning tests and experiments - Performing statistical analysis and fine-tuning using test results - Extending existing ML libraries and frameworks - Keeping abreast of developments in the field - Understanding data structures, data modeling, and software architecture - Demonstrating deep knowledge of math, probability, statistics, and algorithms - Writing robust code in Python, Java, and R - Being familiar with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn) You should have a strong background in machine learning, along with proficiency in Python, Java, and R. Additionally, a good understanding of data structures, data modeling, and software architecture will be essential for this role. Your expertise in math, probability, statistics, and algorithms will be crucial in developing effective machine learning systems. As a Machine Learning Engineer, your role will involve working with Big Data, Neural network (deep learning), and reinforcement learning. Your key responsibilities will include: - Designing machine learning systems - Researching and implementing appropriate ML algorithms and tools - Developing machine learning applications based on requirements - Selecting suitable datasets and data representation methods - Running machine learning tests and experiments - Performing statistical analysis and fine-tuning using test results - Extending existing ML libraries and frameworks - Keeping abreast of developments in the field - Understanding data structures, data modeling, and software architecture - Demonstrating deep knowledge of math, probability, statistics, and algorithms - Writing robust code in Python, Java, and R - Being familiar with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn) You should have a strong background in machine learning, along with proficiency in Python, Java, and R. Additionally, a good understanding of data structures, data modeling, and software architecture will be essential for this role. Your expertise in math, probability, statistics, and algorithms will be crucial in developing effective machine learning systems.