Machine Learning Engineer - MLOps

Placements24; Paarl; Hybrid; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Hybrid work arrangement

Health insurance

Paid time off

Conference access

Training opportunities

Retirement savings plan

Modern Stellenbosch office

Team events

Job summary

Placements24 is seeking a highly skilled Machine Learning Engineer with MLOps expertise to join our client in Stellenbosch, Western Cape. You will design and maintain end-to-end ML pipelines, automate retraining, and ensure reliable deployment of models in production.

You'll work with data scientists and software engineers, containerize apps with Docker, orchestrate with Kubernetes, implement CI/CD, and monitor drift. A strong cloud and scripting background is essential.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related quantitative field.
• Minimum of 3 years of experience in machine learning engineering, with a strong focus on MLOps.
• Proficiency in Python and experience with ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Hands-on experience with MLOps tools and platforms (MLflow, Kubeflow, Seldon Core, SageMaker).
• Strong understanding of CI/CD principles and tools (Jenkins, GitLab CI, GitHub Actions).
• Experience with containerization (Docker) and Kubernetes.
• Familiarity with cloud platforms (AWS, Azure, GCP) and ML services.

Responsibilities

• Design, implement, and maintain robust MLOps pipelines for model training, validation, deployment, and monitoring.
• Automate the machine learning lifecycle, including data ingestion, feature engineering, model training, and deployment.
• Develop and manage infrastructure for scalable ML model serving and inference.
• Implement CI/CD practices for machine learning models.
• Monitor model performance in production, detect drift, and trigger retraining or recalibration as needed.
• Collaborate with data scientists and software engineers to integrate ML models into applications.
• Containerize ML models and applications using Docker and orchestrate with Kubernetes.
• Implement tools for experiment tracking, model versioning, and data versioning.

Skills

Python

CI/CD

Machine Learning

MLOps

Docker

Kubernetes

Git

Communication

Education

Bachelor's or Master's in CS/SE

Tools

MLflow

Kubeflow

Seldon Core

SageMaker

TensorFlow

PyTorch

Job description

About the Role

Our client is a rapidly growing technology firm at the forefront of AI-driven innovation and is seeking a highly proficient Machine Learning Engineer with MLOps expertise to join their talented team in Stellenbosch, Western Cape . This role is central to ensuring the seamless deployment, monitoring, and management of machine learning models in production environments. You will be responsible for building and maintaining robust MLOps pipelines, enabling efficient model retraining, scaling, and operationalization. The ideal candidate will possess a strong understanding of both machine learning principles and software engineering best practices, with a particular focus on automation, CI/CD, and infrastructure. This is an exciting opportunity to work with state-of-the-art technologies, collaborate with cutting-edge AI research, and play a pivotal role in bringing innovative ML solutions to market. We are dedicated to fostering a culture of continuous improvement and technical excellence, providing you with the resources and challenges to thrive. Your contribution will be essential in accelerating the adoption and impact of machine learning across our client's product portfolio.

Key Responsibilities

• Design, implement, and maintain robust MLOps pipelines for model training, validation, deployment, and monitoring.
• Automate the machine learning lifecycle, including data ingestion, feature engineering, model training, and deployment.
• Develop and manage infrastructure for scalable ML model serving and inference.
• Implement CI/CD practices for machine learning models.
• Monitor model performance in production, detect drift, and trigger retraining or recalibration as needed.
• Collaborate closely with data scientists and software engineers to ensure smooth integration of ML models into applications.
• Containerize ML models and applications using Docker and orchestrate them using Kubernetes.
• Implement tools and processes for experiment tracking, model versioning, and data versioning.
• Ensure the reliability, scalability, and efficiency of ML systems in production.
• Troubleshoot and resolve issues related to ML model deployment and performance.

Requirements

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related quantitative field.
• Minimum of 3 years of experience in machine learning engineering, with a strong focus on MLOps.
• 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, Seldon Core, SageMaker).
• Strong understanding of CI/CD principles and tools (e.g., Jenkins, GitLab CI, GitHub Actions).
• Experience with containerization technologies (Docker) and orchestration platforms (Kubernetes).
• Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services.
• Experience with scripting and automation (e.g., Bash, Ansible).
• Solid understanding of software engineering best practices, including version control (Git).
• Excellent problem-solving and communication skills.

Benefits

• Competitive salary with performance-based bonuses.
• Comprehensive health, dental, and vision insurance.
• Hybrid work arrangement offering flexibility.
• Generous paid time off and company holidays.
• Opportunities for professional growth, training, and attending industry conferences.
• Access to cutting-edge MLOps tools and infrastructure.
• Collaborative and innovative work environment.
• Retirement savings plan.
• Modern office facilities in Stellenbosch.
• Wellness programs and team events.