Senior Machine Learning Engineer

Lulalend; Cape Town; On-site; ZAR 600 000 - 900 000; Full time

Job summary

A financial technology company in Cape Town is seeking a Senior Machine Learning Engineer to collaborate with data scientists and enhance ML infrastructure. The ideal candidate will have strong expertise in deploying machine learning systems and experience with Python, SQL, and cloud technologies. This role emphasizes the design and implementation of reliable, efficient ML systems, particularly in the FinTech sector.

Qualifications

• Experience with deploying and managing machine learning systems is essential.
• Strong proficiency in Python and SQL is required.
• Familiarity with Terraform and cloud services required.

Responsibilities

• Consult with data scientists on training ML models.
• Support improvements to ML infrastructure.
• Design systems for throughput and latency needs.
• Implement NFRs for system reliability.

Skills

Productionising ML systems

Training machine learning models

Python

SQL

Terraform

Kafka

Kubernetes

Docker

CI/CD systems

Big Data technologies

MLOps tools

Cloud providers (GCP, AWS, Azure)

Interest in FinTech

Job description

Job title: Senior Machine Learning Engineer

Reporting to: Head of Data Engineering

Location: Cape Town, South Africa

ROLE OVERVIEW

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.

ROLE RESPONSIBILITIES

• 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 DevOps engineering
• Design systems to meet throughput and latency requirements
• Implement NFRs (Non-Functional Requirements) to ensure a high degree of system reliability

THE SKILLS AND EXPERIENCE WE ARE LOOKING FOR

• Prior experience with productionising 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, Kafkaconnect, Pub/Sub.
• Solid experience with Kubernetes, docker, deployment types (canary, blue-green etc.)
• Experience with setting up CI/CD systems using tools such as CircleCI, drone, Github 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 FinTech space

Please note that all appointments are subject to our background checking process, which may include Credit, Criminal and any other job inherent checks.