Role Description The Machine Learning Engineer will design, build, and optimize models to support data-driven decisions and automation for Duvéré Beauvais Peinture. In this part-time remote role, the engineer will develop and evaluate algorithms, implement machine learning pipelines, and collaborate with cross-functional partners to translate business needs into technical solutions. Day-to-day tasks include data preprocessing, feature engineering, model training and validation, performance monitoring, and documenting workflows and results. The engineer will also contribute to experimentation, prototyping new approaches, and maintaining code quality and reproducibility in a collaborative version-controlled environment.
Qualifications
Strong foundation in Computer Science and Algorithms, with the ability to design efficient and scalable solutions.
Hands-on experience with Neural Networks and Pattern Recognition, including building, training, and evaluating models.
Solid understanding of Statistics, including hypothesis testing, probability, and statistical modeling for machine learning.
Proficiency in programming languages commonly used in machine learning (such as Python) and relevant libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow or PyTorch).
Experience with data preprocessing, feature engineering, and working with structured and unstructured data.
Comfort with remote collaboration tools, version control (e.g., Git), and clear technical documentation.
Bachelor’s degree or equivalent experience in Computer Science, Data Science, Engineering, Mathematics, or a related field.
Ability to work independently, manage part-time hours effectively, and communicate complex concepts to non-technical stakeholders.

Machine Learning Engineer

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