Hackajob is collaborating with Sage to connect them with exceptional tech professionals for this role. Sage AI is the global, high-performing AI business unit within Sage. We are building the future of cloud business management by using artificial intelligence to turbocharge our users' productivity. The Sage AI team builds capabilities to help businesses make better decisions and automate processes through embedded, generative, and agentic AI. We are hiring a Director of AI (EMEA) to help us build the next generation of machine learning and AI products for Sage. As a part of our distributed, cross-functional team, you will provide the strategic direction to ML Managers and their direct reports, guiding the entire company’s Data Science and Machine Learning efforts. If you share our excitement for AI, value a culture of continuous improvement and learning, and are excited about working with cutting edge technologies, apply today! This is a hybrid role - three days per week in our Newcastle office. Reporting to the Head of AI and Machine Learning, you will be responsible for: Overseeing multiple ML Managers and helping them to build and scale their teams Helping ML Managers define their teams’ missions, objectives, and road maps Working closely with Product, Data Science, and Engineering teams to shape the future direction of AI at Sage Identifying opportunities to apply AI to new products and/or areas of the business in order to deliver business value Give engineers and data scientists the tools, confidence, and motivation to make decisions independently and drive success of the organization You Have Extensive engineering or data science experience with broad exposure to ML/AI solutions Strong people leadership and team building experience as a senior manager or above, with a demonstrated passion for bringing out the best in a team and helping people grow in their careers Have a strong background in applying cutting edge ML/AI techniques to solve business problems Ability to set and maintain the highest standards for one’s team and oneself Familiarity with fundamentals of probability theory, statistics, and machine learning Knowledge of ML pipelines and engineering architectures Effective communication, negotiation, and execution abilities across teams and stakeholders BS computer science, machine learning, statistics, mathematics or related technical field. Proficiency in ML languages and packages (Python, especially), statistical modelling techniques You may have Experience with MLOps What's It Like To Work Here You will have an opportunity to work in an environment where engineering is central to what we do. The products we build are breaking new ground, and we have a focus on providing the best environment to allow you to do what you do best - solve problems, collaborate with your team and push first class software. Our distributed team is spread across multiple continents, we promote an open diverse environment, encourage contributions to open-source software and invest heavily in our staff. Our team is talented, capable, and inclusive. We know that great things can only be done with great teams and look forward to continuing this direction.