Machine Learning Systems Research Intern at Red Hat working on AI inference and model optimization techniques. Collaborating with experts in the field while gaining hands - on experience in applied ML research.
About the role
- Intermediate Machine Learning Engineer developing and implementing machine learning solutions at Sybrin. Collaborating with teams to enhance product offerings with innovative technology.
Responsibilities
- 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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