Hybrid Intermediate Machine Learning Engineer

at Sybrin

• Job title: Intermediate Machine Learning Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: ZAR 35,000 - ZAR 45,000 per month
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Cyber Security, Docker, Numpy, Pandas, PyTorch, Scikit-Learn, Tensorflow
• Location requirements: Hybrid, Johannesburg, South Africa

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.