Machine Learning Enginee

Role Description This part-time remote Machine Learning Engineer role focuses on developing and deploying machine learning solutions to support financial outsourcing and analytical services. Day-to-day responsibilities include designing and implementing models for tasks such as anomaly detection, forecasting, and pattern recognition in financial data. The role involves collaborating with technical and accounting teams to identify business requirements, preparing and cleaning datasets, and evaluating model performance. The Machine Learning Engineer will also maintain and optimize existing algorithms, document workflows, and support integration of models into production systems.

Qualifications

Candidates should possess strong foundations in Computer Science, including data structures, algorithms, and software engineering principles. Candidates should possess skills in Statistics and Pattern Recognition to analyze complex datasets and derive actionable insights. Candidates should possess experience with Neural Networks and modern machine learning frameworks for building and training predictive models. Candidates should possess practical knowledge of Algorithms related to optimization, clustering, classification, and regression for real-world applications. Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience. Proficiency in programming languages commonly used in machine learning (such as Python or R) and familiarity with libraries like TensorFlow, PyTorch, or scikit-learn. Experience working with financial or business data, and understanding of data privacy and compliance considerations, is beneficial. Strong analytical and problem-solving abilities, effective remote communication skills, and the capacity to work independently with distributed teams.