Salt South Africa
Who you’ll be joining
Think of a global consumer brand that touches millions of people across multiple continents – 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.
They’re scaling AI fast, but safely, and building a hands-on engineering function to turn raw ideas into real products people use every day.
What you’ll be doing
You’re the kind of person who loves building things end-to-end – not just tinkering with models in a notebook, and not just writing APIs in isolation.
In this role, you’ll get to:
Build AI-powered products from the first whiteboard sketch all the way to “Yep, it’s live and people are using it.”
Blend software engineering, ML modelling, and data engineering to create genuinely useful tools.
Work with teams across digital, marketing, operations, and customer experience to understand real problems and craft clear, measurable AI solutions.
Handle everything from classical ML to LLM-powered systems (RAG, prompt design, adapters, etc.).
Integrate models into apps, websites, CRM platforms, internal tools – wherever they’re needed.
Keep things reliable with proper MLOps: monitoring, drift checks, retraining, alerting, and all the good stuff.
Follow a thoughtful governance framework that keeps AI safe, private, fair, and transparent.
Share patterns, build reusable components, and level up the organisation’s AI maturity.
If you enjoy that sweet spot between engineering, ML, and product – you’ll love this.
Who you are
You don’t need the exact same background, but you’ll thrive here if:
You’ve spent around 6+ years working with ML, data science, or software engineering in an applied, production-focused environment.
You’ve deployed real models – not just experiments.
Python and SQL feel like home.
You’re comfortable with ML frameworks (scikit-learn, LightGBM, PyTorch, TensorFlow etc.).
You’ve built or used pipelines, containers, registries, tracking tools, or other MLOps tech.
You’re familiar with cloud platforms (Azure, AWS or GCP – they’re flexible).
You’re great at translating technical work into plain, friendly language.
You like experimenting quickly but also care about building things that last.
You stay curious about new AI developments but lean practical, not hype-driven.
You understand the importance of data privacy and responsible AI.
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