September 17
• Develop, deploy, and optimize machine learning models for data-driven applications. • Design, build, and deploy machine learning models that address specific business needs. • Utilize advanced linear algebra techniques to optimize algorithms for model accuracy and efficiency. • Analyze large datasets and implement mathematical models using techniques from statistics, linear algebra, and calculus. • Collaborate with data engineers and data scientists to ensure seamless integration of machine learning algorithms into production systems. • Research and stay up to date with new developments in machine learning, neural networks, and data science. • Conduct performance evaluations of algorithms and systems, adjusting parameters to enhance results. • Debug, troubleshoot, and refine existing models using knowledge of linear algebra and vector operations. • Write clear and efficient code in Python, R, or other programming languages that effectively implement linear algebra concepts.
• Master’s degree in Computer Science, Mathematics, or a related field. • Strong foundation in linear algebra, with practical experience applying these principles to machine learning. • Proficiency in machine learning frameworks such as TensorFlow, PyTorch, or Keras. • Experience with algorithms that rely on matrix decomposition, eigenvalues/eigenvectors, and other linear algebraic operations. • Deep understanding of optimization techniques and their reliance on linear algebra. • Solid programming skills in Python or similar languages
Apply Now