Description:
Our client is a medium-sized engineering company based in Stellenbosch, specializes in the design, development, integration, implementation, and support of complex hardware and software systems. The client’s Data Science team is looking for a Senior Software Engineer with strong Data Science expertise to help design and implement cutting-edge machine learning and AI features. These features will unlock powerful insights and real value from the massive volumes of data processed by our large-scale, real-time distributed systems.
In this role, you'll collaborate with a team of highly skilled professionals in a dynamic and innovative environment. You’ll be involved from the very beginning of the product lifecycle— evolving ideas, implementation, all the way to deployment at client sites. This is a rare opportunity to build solutions that have real-world impact while working at the intersection of software engineering and data science.
The ideal candidate is a proactive problem solver who takes full ownership of his/her work and thrives in dynamic environments. You are naturally curious, adaptable and eager to learn. Strong communication skills are essential, as you'll be expected to convey complex technical concepts clearly to both technical peers and non-technical stakeholders. You’ll collaborate closely across multiple teams to tackle challenging, real-world problems—always keeping the end user and support teams in mind to ensure that the features you help build are both impactful and practical.
Required:
Bachelor’s degree in Data Science, Computer Science, Engineering, Applied Mathematics, or a related quantitative field with a focus on data science, AI, or machine learning. At least 4 years of hands-on experience in a data science or data-focused software engineering role. Proven experience in the training, deployment and operational support of machine learning or AI models in production environments. Strong programming skills in Python and/or Java, with a solid understanding of software engineering principles and best practices. Proficient in database design and querying, including experience with SQL and working with large datasets. Comfortable working in Unix-based environments, including scripting, troubleshooting and networking. Experience with data wrangling, feature engineering and model evaluation techniques. Experience with version control systems, container technologies, microservice-based architectures, and CI/CD pipelines tailored for machine learning workflows.Preferred:
Masters in Data Science, Computer Science, Engineering, Applied Mathematics, or a related field. Experience working with real-time or event processing systems, such as Apache Kafka. Strong understanding of distributed systems and scalability challenges in big data environments. Practical experience w