MLOps Engineer | Hybrid Work, Scalable ML Deployments

Placements24

Centurion

Hybrid

ZAR 600,000 - 900,000

Full time

6 days ago
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Benefits offered by this job

Hybrid work model
Competitive salary
Professional development

Job summary

Placements24 in Centurion is seeking a skilled MLOps Engineer to bridge ML model development and production deployment. You will design and maintain robust pipelines for continuous integration, delivery, and monitoring of ML models.

You will collaborate with data scientists and engineers to ensure scalable, reliable ML deployments with automated infrastructure in a hybrid work setup in Centurion. A strong software engineering background and passion for automation are essential.

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • 3+ years of software engineering or DevOps experience with MLOps.
  • Proficiency with Python or Bash and containerization.
  • Experience with cloud ML services (AWS/Azure/GCP).
  • Familiarity with ML frameworks and CI/CD.

Responsibilities

  • Develop, automate, and maintain the end-to-end MLOps lifecycle, from data ingestion to model deployment and monitoring.
  • Implement CI/CD pipelines for machine learning models, ensuring smooth and efficient model updates.
  • Build and manage infrastructure for training and serving ML models, leveraging cloud services.
  • Monitor model performance in production, identify drift, and implement retraining strategies.
  • Collaborate with data scientists and software engineers to streamline development and deployment.
  • Ensure reliability, scalability, and security of ML systems in production environments.

Skills

Python
Bash scripting
CI/CD

Education

Bachelor's degree in Computer Science or related field

Tools

Docker
Kubernetes
AWS
TensorFlow
PyTorch
scikit-learn

Job description

Placements24 in Centurion is seeking a skilled MLOps Engineer to bridge ML model development and production deployment. You will design and maintain robust pipelines for continuous integration, delivery, and monitoring of ML models.

You will collaborate with data scientists and engineers to ensure scalable, reliable ML deployments with automated infrastructure in a hybrid work setup in Centurion. A strong software engineering background and passion for automation are essential.

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