Machine Learning Software Engineer

You’ll take a hands-on role building and deploying production-grade machine learning systems, developing scalable software solutions and working closely with clients to turn complex challenges into measurable business outcomes.

• Build and deploy production-grade machine learning software, tools and infrastructure
• Develop reusable, scalable solutions to accelerate AI delivery
• Work across machine learning projects, from initial scoping through to deployment
• Contribute to technical architecture and engineering best practices
• Collaborate with engineers, data scientists, product teams and commercial stakeholders
• Apply machine learning to challenges such as demand forecasting, customer analytics, personalisation, pricing and inventory management
• Advise clients on technical solutions, translating complex ML concepts into practical business outcomes
• Support organisations in adopting AI to improve customer experience and operational efficiency

• Strong Python skills and a solid software engineering background
• Understanding of the full machine learning lifecycle and experience deploying models into production
• Experience with frameworks such as Scikit-learn, TensorFlow or PyTorch
• Hands-on experience with AWS, Azure or GCP, including cloud infrastructure and architecture
• Experience with Docker and Kubernetes for containerisation and orchestration
• Understanding of core machine learning concepts, probability, statistics and experimentation
• Strong communication skills, with the ability to engage technical teams and non-technical stakeholders
• Ability to take ownership of projects and deliver scalable, high-quality solutions in a fast-paced environment

Desirable: Experience working with retail, consumer, ecommerce, marketing, supply chain or customer data.

• Talent Team Screen (30 minutes)
• Pair Programming Interview (90 minutes)
• System Design Interview (90 minutes)
• Commercial Interview (60 minutes)

We welcome applications from candidates with diverse backgrounds. If you don’t meet every requirement but have relevant strengths and a genuine interest in machine learning, we’d still encourage you to apply.