AI/ML Ops Engineer

• Deploy, monitor, and manage ML models in production using best-practice MLOps frameworks and tools.
• Collaborate with data scientists to take prototypes through to production-grade solutions.
• Implement automated model monitoring, retraining, and version control processes to ensure performance stability.
• Optimise model latency and cost efficiency for real-time decision-making in high-volume transactional environments.
• Partner with engineering teams to streamline data flows from operational systems (ERP, WMS, TMS) and ensure data readiness.
• Champion reproducibility, scalability, and operational excellence in AI delivery.

• Bachelor's/Master's in Computer Science, Data Science, Engineering, or related field.
• 4+ years of hands-on experience in MLOps, with a strong background in deploying and managing ML models in production.
• Proven experience in pricing optimisation, shipping, logistics, or supply chain AI solutions.
• Strong Python skills and experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Familiarity with MLOps tools and platforms (MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML).
• Solid understanding of CI/CD, containerisation (Docker, Kubernetes), and cloud-based ML infrastructure.
• Experience working with APIs and integrating ML into operational workflows.

A strong player in the shipping and logistics industry that are looking to expand their AI and ML capabilities.

Opportunity to work at the intersection of AI innovation and real-world logistics challenges.