Who you\u2019ll be joining<\/p>\n
\tThink of a global consumer brand that touches millions of people across multiple continents \u2013 busy digital teams, lots of member interactions, tons of data, and a real appetite for AI that actually does something, not just sit in a slide deck.
\n\tThey\u2019re scaling AI fast, but safely, and building a hands-on engineering function to turn raw ideas into real products people use every day.<\/p>\n
What you\u2019ll be doing<\/p>\n
\tYou\u2019re the kind of person who loves building things end-to-end \u2013 not just tinkering with models in a notebook, and not just writing APIs in isolation.<\/p>\n
In this role, you\u2019ll get to:<\/p>\n
\tBuild AI-powered products from the first whiteboard sketch all the way to \u201cYep, it\u2019s live and people are using it.\u201d
\n\tBlend software engineering, ML modelling, and data engineering to create genuinely useful tools.
\n\tWork with teams across digital, marketing, operations, and customer experience to understand real problems and craft clear, measurable AI solutions.
\n\tHandle everything from classical ML to LLM-powered systems (RAG, prompt design, adapters, etc.).
\n\tIntegrate models into apps, websites, CRM platforms, internal tools \u2013 wherever they\u2019re needed.
\n\tKeep things reliable with proper MLOps: monitoring, drift checks, retraining, alerting, and all the good stuff.
\n\tFollow a thoughtful governance framework that keeps AI safe, private, fair, and transparent.
\n\tShare patterns, build reusable components, and level up the organisation\u2019s AI maturity.
\n\tIf you enjoy that sweet spot between engineering, ML, and product \u2013 you\u2019ll love this.<\/p>\n
Who you are
\nYou don\u2019t need the exact same background, but you\u2019ll thrive here if:<\/p>\n
\tYou\u2019ve spent around 6+ years working with ML, data science, or software engineering in an applied, production-focused environment.
\n\tYou\u2019ve deployed real models \u2013 not just experiments.
\n\tPython and SQL feel like home.
\n\tYou\u2019re comfortable with ML frameworks (scikit-learn, LightGBM, PyTorch, TensorFlow etc.).
\n\tYou\u2019ve built or used pipelines, containers, registries, tracking tools, or other MLOps tech.
\n\tYou\u2019re familiar with cloud platforms (Azure, AWS or GCP \u2013 they\u2019re flexible).
\n\tYou\u2019re great at translating technical work into plain, friendly language.
\n\tYou like experimenting quickly but also care about building things that last.
\n\tYou stay curious about new AI developments but lean practical, not hype-driven.
\n\tYou understand the importance of data privacy and responsible AI.
\n\t\u00a0<\/p>\n
go to method of application \u00bb<\/p>\n
Apply via company website ( ) or<\/p>\n
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