Machine Learning Engineer - Deep Learning Pipelines

About the Role

Our client, a dynamic innovator in AI and emerging technologies, is seeking a skilled Machine Learning Engineer to join their team in Stellenbosch, Western Cape. This role focuses on building and optimizing robust deep learning pipelines that power cutting-edge AI applications. You will be responsible for the end-to-end lifecycle of ML models, from data preprocessing and feature engineering to model training, evaluation, and deployment. The ideal candidate has a strong foundation in software engineering principles combined with practical experience in deep learning frameworks and MLOps practices. You will work closely with researchers and data scientists to translate innovative ideas into scalable, production-ready solutions that drive business value. Join a collaborative environment where your contributions directly impact the development of next-generation AI technologies.

Key Responsibilities

• Design, build, and maintain scalable deep learning training and inference pipelines.
• Implement and optimize data preprocessing and feature engineering workflows.
• Train, evaluate, and fine-tune deep learning models using frameworks like TensorFlow, PyTorch, or JAX.
• Deploy ML models into production environments, ensuring reliability and performance.
• Develop and manage CI/CD pipelines for ML models (MLOps).
• Monitor model performance in production and implement strategies for drift detection and retraining.
• Collaborate with data scientists and researchers to iterate on model development.
• Write clean, efficient, and well-documented code.
• Automate ML workflows and infrastructure management.
• Stay current with advancements in deep learning, ML engineering, and cloud technologies.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• 2-4 years of experience in machine learning engineering or a similar role.
• Proficiency in Python and experience with deep learning frameworks (TensorFlow, PyTorch, JAX).
• Strong understanding of data structures, algorithms, and software engineering best practices.
• Experience with cloud platforms (AWS, Azure, GCP) and their ML services.
• Familiarity with MLOps tools and practices (e.g., Docker, Kubernetes, MLflow, CI/CD).
• Experience with data processing libraries (e.g., pandas, Dask) and SQL.
• Excellent problem-solving and debugging skills.
• Good communication and teamwork abilities.
• Experience with containerization technologies is a plus.

Benefits

Our client offers a competitive salary, regular performance-based reviews, and opportunities for professional growth. Benefits include comprehensive health insurance, retirement savings contributions, and generous paid time off. Employees have access to ongoing training, industry conferences, and career development programs. You'll work in a modern, collaborative office space in , with amenities designed to foster innovation and well-being. Join a leading AI company and contribute to impactful projects.