Designing and developing machine learning models and algorithms.
Performing data preprocessing, data analysis and feature engineering.
Evaluating model performance and tuning hyperparameters for optimization.
Collaborating with data scientists, software engineers, and stakeholders to define project requirements.
Implementing and deploying machine learning models into production.
Conducting code reviews to ensure code quality and best practices.
Debugging and resolving issues related to machine learning models and data pipelines.
Creating and maintaining technical documentation for machine learning projects.
Staying updated with the latest advancements in machine learning and data science.
Requirements
Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field.
Minimum of 3-5 years’ experience.
Experience with frameworks such as PyTorch, TensorFlow, TensorFlow Light, Oynx and Scikit-learn.
Generation of data sets, using data labelling tools such as Roboflow or CVat.
Proficiency in using libraries such as Pandas, NumPy, and SciPy for data manipulation and analysis.
Understanding of key machine learning and statistical algorithms including regression, classification, clustering and neural networks.
Experience in developing, training, and evaluating machine learning models.
Basic knowledge of deploying models using FastAPI and Docker.
Understanding of creating RESTful APIs to integrate ML models into applications.
Proficient in using Git and DVC for version control.
Skills in using libraries such as Matplotlib, Seaborn, and Plotly.
Some experience with the machine learning aspects of cloud services such as AWS, Google Cloud, or Azure.
Experience with integrated development environments (IDEs) like PyCharm or VS Code.
Working knowledge of the principles in ISO 9001:2015 (Quality Management System), ISO/IEC 27001:2022 (Information security, cybersecurity, and privacy management System), ISO/IEC 27701:2019 (Privacy Information Management System), POPIA, GDPR.
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