Engineering Manager: AI/ML at Woolworths

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.

Apply by: 4 July 2025