Machine Learning Engineer - Big Data Analytics
Summary
Designs, trains, and deploys scalable machine-learning models over large datasets for predictive analytics, building big-data pipelines with Spark, Hadoop, and Kafka on cloud platforms (AWS/Azure/GCP). Hybrid role in Rustenburg, South Africa, requiring 3+ years as an ML engineer or data scientist with Python or Scala.
About the Role
Our client is seeking a skilled Machine Learning Engineer with a strong background in Big Data analytics to join their growing team. In this role, you will be instrumental in designing, building, and deploying scalable machine learning models that leverage vast datasets to drive business insights and solutions. You will work with cutting‑edge technologies to process, analyze, and model complex data, enabling data‑driven decision‑making across the organization. This position offers a **hybrid** work model, combining the flexibility of remote work with the benefits of in‑office collaboration. We are looking for an individual who is passionate about data, possesses strong programming skills, and has a proven track record in building and deploying ML solutions in big data environments. The successful candidate will contribute significantly to our client’s advanced analytics capabilities. The **Rustenburg, North West, ZA** location offers a vibrant community and a base for our client’s operational activities.
Key Responsibilities
- Develop, train, and deploy machine learning models for predictive analytics, classification, and clustering.
- Build and maintain robust data pipelines for processing large‑scale datasets.
- Utilize big data technologies (e.g., Spark, Hadoop, Kafka) for data engineering and ML model training.
- Collaborate with data scientists and software engineers to integrate ML models into production systems.
- Optimize ML algorithms and model performance for scalability and efficiency.
- Monitor and maintain deployed ML models, ensuring their accuracy and reliability.
- Explore and experiment with new ML techniques and tools.
- Design and implement A/B testing frameworks for ML model evaluation.
- Work with cloud platforms (AWS, Azure, GCP) for data storage and ML infrastructure.
- Ensure data quality and integrity throughout the ML lifecycle.
Requirements
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field.
- 3+ years of professional experience as a Machine Learning Engineer or Data Scientist.
- Proficiency in programming languages such as Python or Scala.
- Hands‑on experience with ML libraries (e.g., scikit‑learn, TensorFlow, PyTorch).
- Strong experience with big data technologies like Apache Spark, Hadoop & associated ecosystem tools.
- Experience with data warehousing and database technologies (SQL, NoSQL).
- Familiarity with cloud computing platforms (AWS, Azure, GCP).
- Understanding of data structures, algorithms and software engineering best practices.
Benefits
- Competitive salary and annual performance bonus.
- Comprehensive medical, dental, and vision coverage.
- Hybrid work arrangement providing flexibility.
- Generous annual leave and public holidays.
- Retirement fund contribution.
- Professional development budget for courses and conferences.
- Modern office facilities and collaborative workspaces.
- Opportunities for career advancement within a growing company.
- Employee wellness programs.
- Team events and social activities.