Our client is a cutting-edge technology firm building intelligent systems that power next-generation decision-making across financial and industrial domains. With a strong foundation in algorithmic design and real-time data processing, they are seeking a Senior AI Engineer to join their growing team and help scale their AI capabilities across core business functions. As a Senior AI Engineer, you'll work at the intersection of deep learning, infrastructure, and applied research. You'll be responsible for building and deploying AI systems that support real-time inference, experimentation, and continuous learning. This role offers the opportunity to work closely with data scientists, software engineers, and domain experts to solve complex problems using modern AI techniques. If you're passionate about building production-grade AI systems and driving innovation through intelligent automation, this is the role for you. Responsibilities: Build scalable AI pipelines for training, inference, and evaluation. Collaborate across teams to apply AI in automation and optimisation. Maintain MLOps infrastructure for model lifecycle management. Deploy models using frameworks like PyTorch, TensorFlow, or JAX. Integrate AI systems with APIs and real-time data services. Optimize performance across CPU/GPU environments and ensure reliability in production. Contribute to research initiatives involving LLMs, reinforcement learning, and generative models. Requirements: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field. 5 years of experience building and deploying AI/ML systems in production environments. Strong programming skills in Python and familiarity with AI frameworks (e.g., PyTorch, TensorFlow, JAX). Experience with MLOps tools such as MLflow, DVC, or Kubeflow. Familiarity with LLMs, vector databases (e.g., FAISS, Weaviate), and RAG pipelines. Understanding of cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).