AI/ML Engineer

Job Title Machine Learning Engineer Purpose To lead the design and productionisation of Generative AI and LLM-driven applications, utilising GCP and Google’s AI ecosystem. The ML Engineer will architect scalable systems, mentor junior engineers and drive the technical roadmap for integrating Large Language Models into core products, demonstrating innovation and technical excellence across the company’s AI initiative. They will lead and execute elements of the product road map on time and in line with sprint planning deadlines. Reports to Senior Lead Engineer with Line management responsibility Key Relationships Engineering Team Product Team Main Tasks General 1 Design, develop and deploy advanced machine learning and deep learning models and pipelines. 2 Collaborate with cross-functional teams to translate complex business problems into ML-driven solutions. 3 Architect scalable LLM Ops pipelines on GCP (Vertex AI) for model fine-tuning, vector retrieval and low-latency inference. 4 Implement robust LLM evaluation frameworks to monitor output quality (hallucinations, relevance), manage token costs and ensure content safety/governance. 5 Utilise MLOps tools and Google’s Agent Development Kit (ADK) to design autonomous agents and optimise deployment workflows on Vertex AI. 6 Lead the end-to-end development of LLM applications, utilising RAG (Retrieval-Augmented Generation), Agentic workflows and prompt engineering strategies. 7 Monitor, optimize, and fine-tune models in production environments. 8 Contribute to the architecture and design of the company’s AI platform and data infrastructure. 9 Stay up to date with the latest research, emerging technologies, and industry trends in AI and ML Human Resources 10 Mentor junior engineers and data scientists, promoting best practices in ML development. Health