Role Description This is a part-time, remote role for a Machine Learning Engineer. The Machine Learning Engineer will design, implement, and optimize machine learning models to support youth-focused programs, research, and digital initiatives aligned with the SDGs. Day-to-day tasks include collecting and preprocessing data, experimenting with different algorithms and neural network architectures, and evaluating model performance using appropriate statistical methods. The role will involve building prototypes, deploying models into production or pilot environments, and documenting workflows for technical and non-technical stakeholders. The Machine Learning Engineer will collaborate with cross-functional teams, including program managers, designers, and youth leaders, to translate project needs into data-driven solutions.
Qualifications
Strong foundation in Computer Science and Algorithms, including data structures, complexity, and software engineering best practices.
Proficiency in Statistics and Pattern Recognition to design, evaluate, and interpret machine learning models.
Hands-on experience with Neural Networks and modern ML frameworks (e.g., TensorFlow, PyTorch, or similar).
Practical skills in data preprocessing, feature engineering, and model evaluation using real-world datasets.
Experience with Python or another major programming language used in machine learning.
Familiarity with cloud platforms or deployment tools (e.g., AWS, GCP, Azure, or containerization) is an advantage.
Ability to explain complex technical concepts clearly to non-technical stakeholders and work effectively in diverse, remote teams.
Interest in global issues, youth empowerment, and the UN SDGs; prior experience in social impact or NGO projects is a plus.
Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field, or equivalent practical experience.

Machine Learning Enginee

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