We are seeking a highly skilled Machine Learning Engineer to develop, deploy, and optimize machine learning models for large-scale data-driven applications. The ideal candidate will possess deep knowledge of mathematics, especially linear algebra, and have proven experience in applying these principles to solve complex computational challenges.

Responsibilities:

– 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 the fields of 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.

Requirements

– 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