Machine Learning Engineer

We are working on a brand-new project, which is an Innovation Hub/Ai Lab. Requirements: 3-7 years experience building production-grade, scalable AI/ML systems. Very strong Python + ML engineering capability. Experience with supervised/unsupervised ML, deep learning, NLP, Computer Vision and/or GenAI/LLMs you don t necessarily need every area but should have genuine depth. Building end-to-end ML pipelines: ingestion transformation training validation deployment. Production model serving and APIs using FastAPI / Flask. Strong ML system architecture understanding. Experience with real-time and/or batch inference and model performance optimisation. Knowledge of Docker, Kubernetes and CI/CD. Exposure to MLflow and/or Kubeflow for lifecycle management. Deployment onto AWS or Azure. Experience training/deploying traditional ML, neural networks and Agentic AI models. Ideally experience fine-tuning SLMs/LLMs and building more complex AI architectures

Desired Candidate Profile

• 3-7 years experience building production-grade, scalable AI/ML systems.
• Very strong Python + ML engineering capability.
• Experience with supervised/unsupervised ML, deep learning, NLP, Computer Vision and/or GenAI/LLMs you don t necessarily need every area but should have genuine depth.
• Building end-to-end ML pipelines: ingestion transformation training validation deployment.
• Production model serving and APIs using FastAPI / Flask.
• Strong ML system architecture understanding.
• Experience with real-time and/or batch inference and model performance optimisation.
• Knowledge of Docker, Kubernetes and CI/CD.
• Exposure to MLflow and/or Kubeflow for lifecycle management.
• Deployment onto AWS or Azure.
• Experience training/deploying traditional ML, neural networks and Agentic AI models.
• Ideally experience fine-tuning SLMs/LLMs and building more complex AI architectures