Machine Learning Engineer

About Discovery
Discovery’s core purpose is to make people healthier and to enhance and protect their lives. We seek out and invest in exceptional individuals who understand and support our core purpose, and whose own values align with those of Discovery. Our fast-paced and dynamic environment enables smart, self-driven people to be their best. As global thought leaders, Discovery is passionate about innovating in order to not only achieve financial success, but to ignite positive and meaningful change within our society.
About Discovery Bank
Discovery Bank is a bank like no other – a shared-value bank, designed with our clients in mind. We’re all about sharing the value that clients create when they manage their money well, back with them through exceptional interest rates and rewards. Our Vitality Money programme measures how well clients manage their finances, informs them of what it means to be financially healthy, and empowers them with the knowledge to get enhanced rewards for managing their money well. If you’re adaptable, a problem-solver, always questioning the way things are done, passionate about doing what is right, and obsessed with providing a quality service experience, we have a job for you where you can be your best in an environment that’s safe and nurturing.
Job Purpose
We are seeking a talented and enthusiastic Machine Learning Engineer to join our AI Engineering team. As a Machine Learning Engineer, you will be responsible for designing, building, testing, deploying, and maintaining AI and machine learning applications and services. This role places a strong emphasis on developing GenAI-powered solutions for both client-facing applications and internal products, as well as backend systems that directly impact customer experiences. You will work across a range of modalities, including text and voice, to build intelligent, production-ready AI systems. This position offers the opportunity to work with cutting-edge technologies and contribute to the development and automation of AI use cases across the organization. You will work closely with data scientists, product teams, engineers, and other stakeholders to help architect and evolve the bank's modern AI ecosystem, including initiatives such as Discovery AI.
We believe that when our clients are empowered to make better financial decisions, they benefit through improved financial outcomes, and the business benefits alongside them.Personalisation is at the heart of this mission. By leveraging data, analytics, artificial intelligence, and machine learning, we create intelligent, tailored experiences that help clients navigate their financial journeys with confidence. From delivering relevant insights and recommendations to developing innovative products and services, we use technology to solve meaningful problems at scale.
Key Outcomes may include but are not limited to:
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- Generative AI & Machine Learning Development
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- Design and develop Generative AI solutions, including LLM-based applications
- Implement techniques such as prompt engineering, Retrieval-Augmented Generation (RAG), and fine-tuning
- Develop and evaluate machine learning models across supervised, unsupervised, and NLP use cases
- Optimise model performance, reliability, and cost efficiency for enterprise environments
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- Generative AI & Machine Learning Development
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- Deployment & Production
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- Package and deploy AI and GenAI solutions into production (APIs, services, batch workflows)
- Support cloud-based deployments, primarily on Microsoft Azure, including Azure OpenAI and Azure AI services
- Apply MLOps and LLMOps practices such as versioning, monitoring, evaluation, and continuous improvement
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- Deployment & Production
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- Collaboration
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- Collaborate closely with data scientists, actuaries, data engineers, and other software engineers to understand and address their needs.
- Contribute actively to the architecting of our bank's modern Machine Learning data ecosystem.
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- Collaboration
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Education and Experience:
- At least 2-4 years’ working experience as a Software Engineer/Machine Learning Engineer/AI Engineer or related field.
- Bachelor’s degree in engineering or computer science or a related field. Other qualifications will be considered if accompanied by sufficient experience in software engineering.
Technical skills or knowledge:
Core Technical Skills
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- Strong proficiency in Python for AI and machine learning development
- Solid understanding of machine learning fundamentals – preprocessing, training, evaluation
- Hands-on experience with ML frameworks such as scikit-learn, PyTorch, or TensorFlow
- Practical experience with Generative AI and LLMs; familiarity with LangChain, LangGraph, or agent-based frameworks is advantageous
- Strong data handling skills, including SQL and data querying
- Experience deploying ML models or AI services into production environments
- Experience with vector databases and embeddings (e.g., for RAG-based architectures)
- Exposure to AI coding tools such as Cursor or Claude Code is advantageous
- Understanding of DevOps practices, including version control, CI/CD, and testing
- Experience with AI agents is advantageous
Cloud & Platforms
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- Experience with cloud platforms (Azure preferred; AWS or GCP acceptable)
- Familiarity with Azure OpenAI, Azure AI services, or similar GenAI platforms
- Experience with Databricks is advantageous
- Experience building or consuming REST APIs and working with containerisation tools such as Docker
- Exposure to MLOps / LLMOps practices and tools (e.g., MLflow, monitoring, CI/CD pipelines)
EMPLOYMENT EQUITY
The Company’s approved Employment Equity Plan and Targets will be considered as part of the recruitment process. As an Equal Opportunities employer, we actively encourage and welcome people with various disabilities to apply.