Senior Specialist Machine Learning Engineer

## When it comes to putting people first, we're number 1. The number 1 Top Employer in South Africa. Certified by the Top Employer Institute 2026. ## Role Purpose/Business Unit: As a Senior Machine Learning Engineer, you will play a critical role in designing, deploying, and operationalizing scalable machine learning solutions across multiple markets. You will work with cross-functional teams including data scientists, data engineers, software engineers, and product managers to integrate models into production with a robust MLOps lifecycle. This role demands strong experience in ML engineering at scale, advanced automation, real-time model serving, and compliance-aware development. ## Your responsibilities will include: * ML System Design & Architecture: Architect and implement scalable, secure ML pipelines using tools like MLflow, SageMaker, or Databricks. Design reusable templates for batch and real-time inference. * Production Model Deployment: Automate deployment of models into production with CI/CD, containerization (Docker), orchestration (Kubernetes), and feature stores. * Model Monitoring & Governance: Implement real-time model monitoring, drift detection, and lineage tracking to ensure model performance and compliance. * Collaboration & Delivery: Partner with data scientists to translate prototypes into production-ready code. Engage with software and data engineering teams to integrate models into larger systems and APIs. * Automation & Testing: Enforce test-driven development for model code. Implement automated tests for pipelines, accuracy thresholds, and data validation. * Documentation & Knowledge Sharing: Maintain clear technical documentation for models, pipelines, and workflows. Lead internal workshops on MLOps best practices and tooling. * Mentorship: Mentor junior MLEs and data scientists on engineering best practices, reproducibility, and scalable ML system design. ## The ideal candidate for this role will have: * Bachelor’s degree in Computer Science, Data Science, Engineering, Applied Mathematics, or a related field. * Master’s degree or PhD preferred (especially with specialization in Machine Learning, AI, or Distributed Systems). * 8+ years in data science or ML engineering roles, including at least 5 years in production-grade ML deployment and operationalization. * Hands-on experience with distributed computing frameworks and model orchestration at enterprise scale. ## Technical Skills * Languages: Python (mandatory), Bash, SQL; optional: Scala or Java. * ML Libraries & Frameworks: Scikit-learn, XGBoost, TensorFlow, PyTorch. * MLOps & Model Lifecycle: MLflow, SageMaker, Databricks, Kubeflow, Airflow. * Infrastructure: AWS (EC2, S3, SageMaker, IAM, EKS), Terraform, Kubernetes, Docker. * Feature Engineering: Feature Stores (e.g., SageMaker Feature Store, Feast). * Monitoring: Prometheus, Grafana, CloudWatch, Evidently AI. * Security & Compliance: RBAC, KMS, encryption, reproducibility, model versioning. Soft Skills * Strategic problem-solver with strong system thinking. * Excellent communication and technical storytelling across technical and business stakeholders. * Comfortable working in agile squads and fast-paced delivery environments. * Passionate about enabling ML at scale and setting engineering standards. Preferred Certifications * AWS Certified Machine Learning – Specialty * Databricks Certified ML Professional * Kubernetes Administrator (CKA) * MLflow or MLOps specialization (e.g., DeepLearning.AI, Coursera) ## We make an impact by offering: * Enticing incentive programs and competitive benefit packages * Retirement funds, risk benefits, and medical aid benefits * Cell phone and data benefits, advantages fibre connection discounts, and exclusive staff discounts offered in collaboration with partner companies Closing date for Applications: 30 July 2026. The base location for this role is Midrand, Vodacom Campus. The company's approved...