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