About the Role
This is an opportunity to join a high-impact AI team building real, customer-facing products at scale. You'll sit at the intersection of data science and engineering, taking cutting-edge models from concept through to production and ensuring they perform reliably in real-world environments.
You'll work across recommendation systems, dynamic pricing engines, and emerging GenAI and agent-based applications, helping shape how intelligent systems are delivered to millions of users.
This is a hands-on role in a fast-moving team, ideal for someone who enjoys building, shipping, and seeing their work drive measurable outcomes.
Key Responsibilities
* Take machine learning models from POC through to robust, scalable production systems
* Build and optimise end-to-end ML pipelines, including training, inference, and monitoring
* Deploy and manage AI solutions in cloud environments, ideally GCP and Vertex AI
* Develop and experiment with GenAI and agent-based systems, including customer and internal analytics use cases
* Collaborate closely with Data Scientists to productionise models and improve performance
* Implement best practices across CI/CD, version control, testing, and model lifecycle management
* Continuously improve system performance, scalability, and reliability in production environments
What You'll Bring
* Proven experience deploying machine learning models into production environments
* Strong Python and ML engineering capability, with experience building scalable systems
* Experience working with APIs, microservices, and batch or real-time inference pipelines
* Exposure to MLOps practices, including CI/CD, Docker, and monitoring frameworks
* Experience working with GenAI, LLMs, or agent-based architectures
* Cloud experience, GCP preferred, though AWS or Azure backgrounds are also valuable
* A product mindset, focused on delivering real outcomes rather than just models
Why This Role
* Work on AI systems that directly impact customer experience at scale
* Strong focus on production, not just experimentation
* Exposure to modern GenAI and agent-based architectures
* Small, high-performing team with fast decision-making and real ownership
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