Senior ML Engineer

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

Job summary

A leading company seeks a Senior ML Engineer for a 12-month contract in Cape Town. The role involves designing, developing, and optimizing machine learning models using AWS technologies. Candidates should have over 5 years of experience and strong technical skills in Python and related libraries, with a preference for those with banking industry experience.

Qualifications

• 5+ years of experience in Machine Learning Engineering.
• Strong expertise in Python, PySpark, SQL, and ML libraries.
• Experience with AWS ML services.

Responsibilities

• Design, develop, and deploy ML models in AWS SageMaker and EKS.
• Optimize ML models for real-time decisioning in high-traffic environments.
• Automate model retraining and monitoring using AWS tools.

Skills

Python

PySpark

SQL

TensorFlow

PyTorch

Scikit-learn

AWS SageMaker

AWS EKS

AWS Lambda

AWS Redshift

Control-M

Terraform

OpenSearch

FluentBit

Prometheus

Grafana

AWS CloudWatch

Tools

GitHub Actions

Docker

Kubernetes

Job description

Senior ML Engineer - 12 MonthContract

Key Responsibilities

• Design, develop, and deploy ML models in AWS SageMaker and EKS.

• Optimize ML models for real-time decisioning in high-traffic environments.

• Ensure models comply with regulatory and security standards.

• Build and maintain CI/CD pipelines for ML model deployments.

• Automate model retraining, monitoring, and logging using AWS Lambda, Terraform, and Control-M jobs.

• Implement observability tools like OpenSearch, FluentBit, Prometheus, Kibana, Grafana, and AWS CloudWatch.

• Develop ETL/ELT pipelines for data preprocessing and feature engineering.

• Work with AWS Redshift to process large-scale datasets for model training.

• Monitor ML models running 24/7 in production, ensuring reliability and high availability.

• Work closely with engineering teams to troubleshoot and optimize production systems.

• Participate in an on-call rotation for urgent ML pipeline issues.

• Collaborate with data scientists, decision engineers, and credit engineers to align ML solutions with business needs.

• Take ownership of ML solutions and provide guidance to junior engineers.

• Contribute to the ongoing AI/ML strategy within the business.

Required Skills & Qualifications:

Technical Skills:

• 5+ years of experience in Machine Learning Engineering.

• Strong expertise in Python, PySpark, SQL, and ML libraries (TensorFlow, PyTorch, Scikit-learn).

• Experience with AWS ML services (Amazon SageMaker, EKS, Lambda, Redshift, Control-M, Terraform).

• Experience with MLOps practices (CI/CD pipelines with GitHub Actions, Docker, Kubernetes).

• Proficiency in observability & monitoring tools: OpenSearch, FluentBit, Kibana, Prometheus, Grafana, CloudWatch.

• Strong understanding of real-time ML applications in financial environments.

• Experience in building and maintaining ETL pipelines in a cloud environment.

Soft Skills:

• Leadership & Ownership Ability to work independently and drive ML initiatives.

• Problem-Solving Ability to troubleshoot ML model failures in production.

• Strong Communication Work effectively with cross-functional teams.

• Agility Adapt to a fast-paced, high-stakes environment.

• Banking Industry Experience Preferred.