Machine Learning Engineer - MLOps Specialist

Placements24; Benoni; Hybrid; ZAR 900,000 - 1,200,000; Full time

Benefits offered by this job

Competitive salary

Health insurance

Hybrid work model

Professional development opportunities

Job summary

Placements24 in Benoni, Gauteng seeks a skilled Machine Learning Engineer with a strong MLOps background to join their hybrid team. You will build and maintain scalable ML pipelines, deploy models to production, and ensure reliability across systems.

Collaborate with data scientists and software engineers, implement ML CI/CD, monitor model performance, and manage drift and retraining with best practices for versioning, testing, and documentation.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related quantitative field.
• 3+ years of experience in Machine Learning Engineering with a strong MLOps focus.
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Experience with ML platforms (MLflow, Kubeflow, SageMaker, Azure ML).
• Experience with Docker and Kubernetes.

Responsibilities

• Design, build, and maintain scalable MLOps pipelines for model training, deployment, and monitoring.
• Automate ML workflows including data preprocessing, model validation, and A/B testing.
• Manage ML model serving infrastructure for high availability and low latency.
• Develop CI/CD pipelines for ML models.
• Monitor production models, detect drift, and plan retraining.
• Collaborate with data scientists to optimize models for production.
• Apply best practices for version control, testing, and documentation of ML systems.
• Troubleshoot deployment and performance issues.

Skills

MLOps

Python

CI/CD

ML model deployment

Collaboration

Education

Bachelor's or Master's degree in Computer Science or Engineering

Tools

TensorFlow

PyTorch

scikit-learn

MLflow

Kubeflow

SageMaker

Azure ML

Docker

Kubernetes

AWS

GCP

Job description

About the Role

Our client, a rapidly growing tech company, is seeking a skilled Machine Learning Engineer with a strong MLOps background to join their team in Benoni, Gauteng . This hybrid role is essential for building and maintaining robust, scalable, and reliable machine learning pipelines and infrastructure. You will be responsible for streamlining the deployment, monitoring, and management of machine learning models in production environments. The ideal candidate will possess a blend of software engineering best practices and deep understanding of machine learning concepts and tools. You will work closely with data scientists and software engineers to ensure the smooth operation and continuous improvement of our client's AI systems. This position offers a fantastic opportunity to work with modern MLOps tools and contribute to the efficiency and effectiveness of our client's AI initiatives.

Key Responsibilities

• Design, build, and maintain scalable MLOps pipelines for model training, deployment, and monitoring.


• Automate machine learning workflows, including data preprocessing, model validation, and A/B testing.


• Implement and manage infrastructure for ML model serving, ensuring high availability and low latency.


• Develop and deploy CI/CD pipelines specifically for machine learning models.


• Monitor model performance in production, identify drift, and implement retraining strategies.


• Collaborate with data scientists to optimize models for production environments.


• Implement best practices for version control, testing, and documentation of ML systems.


• Troubleshoot and resolve issues related to ML model deployment and performance.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.


• 3+ years of experience in Machine Learning Engineering or a related role with a strong MLOps focus.


• Proficiency in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).


• Hands-on experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, SageMaker, Azure ML).


• Experience with containerization technologies (Docker, Kubernetes).


• Strong understanding of cloud platforms (AWS, Azure, GCP) and their ML services.


• Solid software engineering skills, including CI/CD, version control (Git), and scripting.


• Excellent problem-solving and debugging abilities.

Benefits

Our client provides a competitive salary, comprehensive health insurance, and opportunities for professional development and certifications. The hybrid work model allows for flexibility, balancing collaborative office time with remote work convenience. Employees benefit from a culture that values innovation, continuous learning, and work-life balance. Join our dynamic team in Benoni, Gauteng , and contribute to the operational excellence of our cutting-edge AI systems.