Senior MLOps Engineer (Python & SQL), CI/CD

Datafin; Cape Town; On-site; ZAR 800,000 - 1,200,000; Full time

Job summary

A reputable Independent Asset Management Firm based in Cape Town is seeking an experienced MLOps Engineer. The ideal candidate will have over 5 years of practical experience in delivering ML projects from concept to production, with strong skills in Python and SQL. You'll be designing MLOps infrastructure, leading full-lifecycle ML projects, and mentoring junior team members while promoting best practices in data science. The role emphasizes innovation, collaboration, and the drive to continuously improve data science culture across the organization.

Qualifications

• 5+ years delivering commercially driven ML projects from concept to production.
• Strong grasp of data warehousing and modelling concepts.
• Ability to build meaningful relationships and work in cross-functional teams.

Responsibilities

• Architect and automate end-to-end ML pipelines in Azure or DataBricks.
• Lead full-lifecycle ML projects from ideation to monitoring.
• Translate business questions into data-science roadmaps.
• Embed security and efficiency into the development process.

Skills

Expert Python

Solid SQL

Modern development practices (Git, tests, code review, CI/CD)

Hands-on design of MLOps pipelines

Collaboration with Data Engineering

Familiarity with Deep-Learning frameworks (TensorFlow/PyTorch)

Vector databases knowledge

Passion for upskilling others

Excellent communication skills

Tools

Docker

Kubernetes

Azure

DataBricks

Mosaic

BigQuery

Spark

Kafka

dbt

Job description

A reputable Independent Asset Management Firm based in Cape Town is seeking an experienced MLOps Engineer. The ideal candidate will have over 5 years of practical experience in delivering ML projects from concept to production, with strong skills in Python and SQL. You'll be designing MLOps infrastructure, leading full-lifecycle ML projects, and mentoring junior team members while promoting best practices in data science. The role emphasizes innovation, collaboration, and the drive to continuously improve data science culture across the organization.