Machine Learning Enginee

Role Description This part-time remote Machine Learning Engineer role at Comunidad Petrolera de Colombia focuses on designing, implementing, and evaluating machine learning models for industry-specific data. On a day-to-day basis, the Machine Learning Engineer will collect, clean, and prepare datasets; prototype and optimize algorithms; and build predictive models for tasks such as pattern detection, risk assessment, and operational efficiency. The role includes collaborating with cross-functional teams to translate business requirements into technical solutions, conducting experiments to compare model performance, and documenting methodologies and results. The Machine Learning Engineer will also contribute to deploying models into production environments, monitoring their performance, and iteratively improving them based on feedback and new data.
Qualifications
Strong foundation in Computer Science, including data structures, Algorithms, and software development best practices.
Applied knowledge of Statistics and Pattern Recognition for building robust, data-driven models.
Hands-on experience with Neural Networks and modern machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Proficiency in programming languages commonly used in machine learning (such as Python or R) and in working with version control tools.
Ability to design, train, validate, and deploy machine learning models in real-world, production-like environments.
Strong analytical and problem-solving skills, with the ability to interpret complex datasets and communicate insights clearly.
Experience with cloud platforms or MLOps tools for model deployment and monitoring is an advantage.
Bachelor’s degree or equivalent experience in Computer Science, Data Science, Engineering, Mathematics, or a related field.

Work arrangement
Yes