Senior ML Engineer
Boardroom AppointmentsCape Town, Western Cape, South Africa
Posted January 5, 2026
Contract / Temporary
About the Company
Boardroom Appointments, founded in 1989, is a global talent solutions provider delivering recruitment, contract staffing, project staffing, temporary employment, training, HR consultancy, and expatriate mobility services across Africa, EMEA, the Americas, and Europe. Leveraging a deep industry focus that spans FMCG, finance, manufacturing, oil & gas, healthcare, logistics, IT, renewable energy, retail, agriculture, government, and call‑center services, the firm custom‑builds solutions that match each client’s unique talent needs. With a worldwide candidate database and a team of seasoned recruitment and HR professionals, Boardroom Appointments offers end‑to‑end services—from executive search and people analytics to payroll outsourcing and workforce management—ensuring seamless, high‑quality placements that let clients concentrate on their core business. Their distinctive value lies in a partnership model that blends industry expertise, data‑driven insights, and a culture of passion and professionalism to deliver flawless, long‑lasting results.
Job Description
Senior ML Engineer designing, developing, and deploying ML models in AWS SageMaker and EKS, with a focus on real-time decisioning, regulatory compliance, and CI/CD pipelines.
Requirements
- 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.
Benefits
- 12 Month Contract