Senior Machine Learning Engineer

we deliver value to our customers with solutions that simplify complex decisioning using data, ML and AI. As a Machine Learning Engineer (MLE), you will work within cross-functional squads to deliver scalable, production-ready machine learning solutions. Your work will support ML use cases that drive business value across areas such as customer value management, customer experience, revenue generation, fraud detection, and intelligent automation.

You will be responsible for designing, developing, deploying, and maintaining ML models and pipelines.

Manage end-to-end productionisation of machine learning use cases, ensuring code hygiene, feature selection, and deployment readiness.

Apply and maintain productionisation checklists and other documentation to standardise handover processes from data scientists.

Ensure code is tested in ML framework environments and structured for production deployment.

Configure and manage Airflow DAGs to visualise and orchestrate task dependencies.

Participate in code reviews, QA testing, and deployment walkthroughs with MLOps.

Support model retraining schedules and automate endpoint updates for real-time scoring use cases.

Propose and implement process improvements to streamline handovers and reduce delays.

Promote awareness and best practices for coding, tooling and testing among data scientists.

Experience building, deploying, and maintaining machine learning systems in production environments.

Proficiency in Python and Spark for data processing and model development.

Experience with Airflow for workflow orchestration and DAG configuration.

Familiarity with Git Lab and repository management practices.

Knowledge of database systems such as Hive, Mongo

DB and Cassandra.

Experience with QA processes, code reviews, and deployment procedures.

Strong collaboration skills to work with cross-functional teams.

Ability to manage and optimise productionisation workflows and checklists.

Keeping technical docs up to date for smooth handovers.

Honours degree in Computer Science, Engineering, or a related field; or equivalent professional experience in machine learning engineering.

Google Cloud Platform (GCP) ML Certification or equivalent is advantageous.

Experience with GCP-native ML tools such as Vertex AI and Model Garden is advantageous.

Exposure to ML frameworks.

At Spatialedge, you will have the opportunity to work with a team of experienced professionals and gain invaluable insights into the world of AI and data-driven decision-making. You will be involved in real projects that make a significant impact on our clients' businesses, including renowned companies in South Africa and abroad!