Senior Machine Learning Engineer

Senior Machine Learning Engineer

Reporting to: Head of Data Engineering

Location: Cape Town, South Africa

You’ll work at the intersection of data science and engineering to build, deploy, and scale machine learning systems. This includes improving ML infrastructure, designing reliable real‑time data systems, and ensuring models run efficiently and reliably in production.

• Consult with data scientists on training machine learning models.
• Support improvements and additions to the ML infrastructure, including getting your hands dirty with data engineering and Dev Ops engineering.
• Design systems to meet throughput and latency requirements.
• Implement NFRs (Non‑Functional Requirements) to ensure a high degree of system reliability.

• Prior experience with product ionising ML systems is a must.
• Prior experience training machine learning models is highly desirable.
• Advanced knowledge of Python and familiarity with SQL.
• Good working knowledge of Terraform for Infrastructure as Code (IaC).
• A solid understanding and hands‑on experience with real‑time and event‑driven systems such as Kafka, Kafka Connect, Pub/Sub.
• Solid experience with Kubernetes, Docker, and deployment types (canary, blue‑green, etc.).
• Experience with setting up CI/CD systems using tools such as Circle
  
  CI, Drone, Git Hub Actions, ArgoCD.
• Working experience with Big Data technologies such as Spark, Dataflow, and Flink.
• Experience with system design – keeping performance and efficiency in mind, whilst aware of trade‑offs.
• Experience applying software engineering rigor to ML, including CI/CD/CT, unit‑testing, automation, etc.
• Hands‑on experience with some MLOps tools such as Kubeflow, DVC, MLflow.
• Experience with cloud providers, such as GCP, AWS, or Azure.
• Prior experience or a strong interest in the Fin Tech space.

Mid‑Senior level

Full‑time

Engineering and Information Technology

Banking