Machine Learning Operations (MLOps) Engineer

Placements24; Canterbury; On-site; NZD 100,000 - 150,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive benefits package

Job summary

Placements24 is seeking a skilled MLOps Engineer to improve the reliability and scalability of AI systems in Queenstown. You will bridge model development and deployment, automating the entire ML lifecycle to ensure robust, efficient production solutions.

Join a growing tech team focused on best practices in AI deployment and operations, collaborating with data scientists and engineers to optimize infrastructure, monitoring, and cost efficiency in a dynamic environment.

Qualifications

• Bachelor's degree in CS, Engineering, or a related field.
• 3+ years of experience in software engineering, DevOps, or MLOps.
• Proficiency in Python and cloud platforms (AWS, Azure, GCP).
• Experience with containerization (Docker, Kubernetes).
• Familiarity with ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Understanding of ML lifecycle and deployment challenges.

Responsibilities

• Design, build, and maintain CI/CD pipelines for ML models.
• Automate deployment, monitoring, and management of ML models in production.
• Implement infrastructure for data/versioning and experiment tracking.
• Monitor ML performance in production and resolve issues.
• Collaborate with data scientists and engineers for lifecycle management.
• Optimize ML infrastructure for cost-efficiency and scalability.

Skills

Python scripting

CI/CD pipelines

Cloud platforms

Docker & Kubernetes

ML frameworks

MLOps tools

Team collaboration

Education

Bachelor's degree in Computer Science/Engineering

Tools

Docker

Kubernetes

TensorFlow

PyTorch

Job description

About the Role

Our client is seeking a skilled Machine Learning Operations (MLOps) Engineer to enhance the reliability and scalability of their AI systems in Queenstown . This role bridges the gap between machine learning model development and deployment, focusing on automating and streamlining the entire ML lifecycle. You will play a vital part in ensuring our AI solutions are robust, efficient, and consistently performant in production. Join a growing technology team committed to best practices in AI deployment and operations in the Eastern Cape .

Key Responsibilities

• Design, build, and maintain CI/CD pipelines for machine learning models.
• Automate the deployment, monitoring, and management of ML models in production environments.
• Implement infrastructure for data versioning, model versioning, and experiment tracking.
• Monitor ML model performance in production, identify issues, and implement solutions.
• Collaborate with data scientists and engineers to ensure smooth model integration and lifecycle management.
• Optimize ML infrastructure for cost-efficiency and scalability.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in software engineering, DevOps, or MLOps.
• Proficiency in scripting languages (e.g., Python) and cloud platforms (AWS, Azure, GCP).
• Experience with containerization technologies (Docker, Kubernetes).
• Familiarity with ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Understanding of ML lifecycle and deployment challenges.
• Experience with MLOps tools and platforms is highly desirable.

Benefits

• Competitive salary and comprehensive benefits package.
• Opportunity to work at the forefront of MLOps and AI deployment.
• Professional development in cloud technologies and ML infrastructure.
• A collaborative and supportive work environment in Eastern Cape .
• Direct impact on the operational efficiency of AI systems in Queenstown .