AI/ML Engineer

About the role

The AI/ML Engineer will design, develop, and deploy machine-learning models that power intelligent automation and data-driven decision-making across the business. Working closely with software engineers, data analysts and product owners, you will translate business problems into scalable AI solutions.

Key responsibilities

• Design, build and deploy ML models for classification, regression, NLP, computer vision or time-series forecasting.
• Prepare, clean and engineer features from structured and unstructured data sets.
• Package models with Docker and serve them via Flask/FastAPI or Kubernetes, implementing CI/CD pipelines using MLflow, Airflow or Kubeflow.
• Monitor production models for drift, latency and performance, and continuously improve them.
• Collaborate with stakeholders to define AI use cases such as recommendation engines, chat-bots or fraud detection.
• Stay current with research and experiment with cutting-edge techniques like large language models and generative AI.
• Document experiments, pipelines and best practices to ensure reproducibility and compliance.

Required profile

• 3–5 years of hands-on experience developing and deploying machine-learning models.
• Strong understanding of supervised, unsupervised and deep-learning algorithms.
• Proven ability to work in cross-functional teams and communicate technical concepts to business audiences.

Required skills

• Python programming
• TensorFlow or PyTorch frameworks
• Docker containerisation
• Flask or FastAPI for model serving
• Kubernetes orchestration
• CI/CD tools such as MLflow, Airflow or Kubeflow