Machine Learning Specialist

About the role

Operationalise machine learning models and AI capabilities into reliable, scalable, and secure production systems that power paid risk intelligence products. 

Key responsibilities

ML Systems & Deployment 

• Design and build scalable model training, deployment, and inference pipelines 

• Deploy models into production using CI/CD, containerisation, and cloud infrastructure 

• Ensure models meet performance, latency, and reliability requirements 

MLOps & Lifecycle Management 

• Implement model versioning, monitoring, and automated retraining mechanisms 

• Detect and respond to model drift, data drift, and performance degradation 

• Establish operational standards for AI systems 

Collaboration with Data Science & Product 

• Partner with Data Scientists to productionise and scale models 

• Work with Product and Engineering teams to integrate ML into customer‑facing products 

• Translate experimental work into robust production assets 

Governance, Security & Ethics 

• Ensure ML systems comply with privacy, security, and regulatory requirements 

• Support explainability, auditability, and responsible AI practices 

• Document models and operational decisions clearly 

Job Profile – Required Skills and Knowledge

• 8+ years experience in ML engineering, MLOps, or software engineering roles 

• Strong software engineering skills in Python and cloud environments 

• Hands‑on experience with ML platforms (MLflow, Kubeflow, SageMaker) and Kubernetes 

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field
• MS in Big Data, AI or relevant fields