Machine Learning Engineer

ABOUT THE OPPORTUNITY

Our client is a forward-thinking cloud solutions provider operating at the forefront of enterprise AI and digital transformation in South Africa. As they scale their capabilities and deepen their footprint across key industry verticals, they are looking for a Machine Learning Engineer to join a high-impact team building intelligent, scalable solutions that directly influence business outcomes — from fraud detection and revenue optimisation to next-generation AI-powered customer experiences.

This is not a maintenance role. You will be architecting, building, and deploying production-grade AI systems in a complex, regulated environment — and you will be doing it alongside some of the sharpest minds in the industry.

WHAT YOU'LL DO

• Design and deploy machine learning models across supervised, unsupervised, and deep learning paradigms to solve high-stakes business problems
• Build and optimise Large Language Model (LLM) solutions using GPT, BERT, and open-source alternatives — including RAG pipelines, prompt engineering, PEFT, and LoRA fine-tuning
• Develop Agentic AI systems and AI chatbots that integrate seamlessly with legacy banking infrastructure
• Architect and maintain ETL pipelines, data lakes, and feature engineering workflows that power model training and inference at scale
• Collaborate with data engineers and platform teams to deploy models via Docker, Kubernetes, and cloud platforms (AWS, Azure AI Foundry, Azure ML Studio)
• Drive measurable business impact through predictive modelling, customer segmentation, fraud detection, and A/B testing frameworks
• Contribute to the full MLOps lifecycle — from experimentation through to model monitoring and continuous improvement

WHAT YOU NEED TO BRING

Core AI & ML

• Proven expertise across the ML spectrum: supervised/unsupervised learning, deep learning, generative AI, NLP, GANs, and transfer learning
• Hands-on experience with LLMs and GenAI frameworks — LangChain, LangGraph, LangServe, Hugging Face, OpenAI APIs
• Strong grounding in vector databases and retrieval-augmented generation (RAG) architectures, including FAISS

Programming & Tooling

• Python (primary), with working knowledge of SQL, Java, or Scala
• Proficiency with ML frameworks: TensorFlow, PyTorch
• API and application development: FastAPI, Streamlit

Big Data & MLOps

• Experience with distributed data processing: Apache Spark, Hive, PIG
• Workflow orchestration via Airflow
• Containerisation and deployment: Docker, Kubernetes
• Cloud-native ML: AWS and/or Azure AI Foundry / Azure ML Studio

Data Engineering

• Solid understanding of data warehousing, data lake architecture, and feature stores
• Ability to design robust ETL pipelines from raw data to model-ready datasets

Business Acumen

• Track record of translating model outputs into tangible business value — revenue uplift, fraud reduction, customer intelligence
• Comfortable operating in regulated, enterprise environments with legacy system constraints

WHY THIS ROLE

This engagement places you inside one of South Africa's most consequential AI programmes: in a sector where the stakes are real and the data is rich. If you thrive in ambiguity, move fast without sacrificing rigour, and want your work to matter beyond a Jupyter notebook, this is the contract for you.