Machine Learning Engineer (MLOps / AI Platform)

An excellent Machine Learning Engineer (MLOps / AI Platform) opportunity has just arisen within a cutting-edge AI environment. Job Purpose: Build and scale machine learning systems from experimentation to reliable production deployment. Job Responsibilities: Design and deploy machine learning solutions from data pipelines to production systems. Build scalable pipelines for training, testing, and serving AI models reliably. Work with data scientists to convert research code into production-ready applications. Manage model lifecycle including versioning, monitoring, performance tracking, and continuous improvements. Implement modern AI solutions including LLMs, agents, and retrieval-based systems. Job Requirements: 7+ years' Python programming experience building scalable and maintainable applications. Experience deploying machine learning models into production environments using modern tools. Familiarity with cloud platforms, containers, and CI/CD pipelines for automation. Understanding of machine learning concepts, data processing, and model evaluation techniques. Experience or interest in LLMs, AI agents, or modern generative AI technologies. The successful Machine Learning Engineer (MLOps / AI Platform) must possess strong Python skills, production ML experience, and interest in modern AI technologies such as LLMs and automation workflows. Work on real-world AI systems including LLMs, automation workflows, and scalable ML platforms. EA Reg. No. 25C2690 | EA license No. R1330510