Engineering Manager: AI/ML
Listing reference: woolw_001262
Listing status: Under Review
Apply by: 4 July 2025
Position summary
Industry: FMCG & Supply Management
Job category: FMCG, Retail, Wholesale and Supply Chain
Location: Western Cape
Contract: Permanent
Remuneration: Market Related
EE position: No
Introduction
The Engineering Manager: AI/ML is responsible for leading and scaling the machine learning engineering function within the organisation. This role focuses on the development, deployment, and operationalisation of ML models, ensuring they are robust, scalable, and effectively integrated into business processes. Working closely with Data Science, Data Engineering, Platform and Cloud Architecture teams, the Engineering Manager: AI/ML ensures that ML initiatives drive value while adhering to best practices in MLOps, model governance, and performance optimisation. This position combines technical expertise, strategic vision, and leadership to develop a high-performing ML engineering team and deliver impactful AI solutions.
Job description
- Work closely with MLOps Engineers in the Platform team to ensure adherence to established MLOps policies and frameworks.
- Lead the end-to-end deployment of machine learning models, ensuring reliability, scalability, and business impact.
- Ensure seamless integration of ML models into production systems and data pipelines.
- Work collaboratively with Data Science team to translate research prototypes into production-grade solutions.
- Implement governance frameworks for model performance tracking, versioning, and continuous learning.
- Build and manage a high-performing ML Engineering team, fostering a culture of innovation and excellence.
- Champion the use of cloud-based ML infrastructure (AWS SageMaker, Databricks, Kubernetes, etc.) for scalable deployment.
- Optimize model inference pipelines, ensuring they are efficient and cost-effective in production environments.
- Develop strategic partnerships with business units to align AI/ML initiatives with company objectives.
- Maintain compliance with ethical AI principles, security, and data privacy in all ML-driven applications.
Minimum requirements
- Master's or Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or related fields.
- Minimum 6 years in machine learning engineering, with at least 2 years in a leadership role.
- Strong experience in MLOps, CI/CD for ML models, and cloud-based AI solutions.
- Proficiency in Python, TensorFlow, PyTorch, and MLflow.
- Expertise in cloud ML services (AWS SageMaker, Azure ML).
- Experience with containerisation and orchestration (Docker, Kubernetes).
- Strong background in ML model optimisation, inference serving, and monitoring.
- Understanding of data engineering workflows, feature engineering, and model deployment pipelines.
- Ability to lead and mentor ML engineers and collaborate with cross-functional teams.
- Strong stakeholder management, bridging the gap between business and technical teams.
- Excellent problem-solving skills and ability to drive AI adoption across the organisation.
ADDITIONAL CRITERIA
- Strategic Thinking: Ability to align ML initiatives with broader business goals.
- Collaboration & Communication: Works effectively across data science, engineering, and business teams.
- Innovation-Driven: Keeps up with emerging trends in AI/ML, experimenting with new techniques and technologies.
- Problem-Solving: Proactively identifies bottlenecks in ML pipelines and ensures continuous improvements.
- Adaptability: Thrives in a fast-paced AI-driven environment, adjusting strategies as needed.
- Cultural Fit: Demonstrates integrity, accountability, and a commitment to fostering a high-impact AI/ML team.
