Machine Learning Operations (MLOps) Engineer

Placements24; Kimberley; Hybrid; CAD 90,000 - 140,000; Full time

Benefits offered by this job

Hybrid work model

Health insurance

Retirement plan

Learning opportunities

Job summary

Placements24 is seeking a skilled MLOps Engineer in Kimberley to bridge ML development and production deployment. You will build and maintain infrastructure and tools enabling scalable, reliable AI systems in a hybrid work environment.

The role requires strong software engineering and DevOps background, with expertise across ML lifecycles and cloud/container tech. Collaborative culture and ongoing learning opportunities are emphasized.

Qualifications

• Bachelor's degree in CS, Engineering, or a related field.
• Proven experience in MLOps, DevOps, or SRE.
• Proficiency with cloud platforms (AWS, Azure, GCP) and Docker/Kubernetes.
• Experience with scripting languages (Python, Bash) and IaC tools.
• Understanding of ML concepts and workflows.

Responsibilities

• Design, implement, and manage CI/CD pipelines for machine learning models.
• Develop and maintain infrastructure for model training, deployment, and monitoring.
• Automate ML workflows, including data validation, model training, and performance tracking.
• Collaborate with data scientists and software engineers to streamline the ML lifecycle.
• Ensure the scalability, reliability, and security of ML production systems.

Skills

MLOps

DevOps

SRE

Docker

Kubernetes

Python

Bash

IaC

Cloud Platforms

ML Lifecycle

Education

Bachelor's degree in CS/Engineering

Tools

Cloud (AWS/Azure/GCP)

Job description

About the Role

Our client is seeking a skilled Machine Learning Operations (MLOps) Engineer to join their dynamic technology team in Kimberley. This role is vital for bridging the gap between machine learning model development and production deployment. You will be responsible for building and maintaining the infrastructure, tools, and processes that enable the efficient, reliable, and scalable deployment of machine learning models. The ideal candidate has a strong background in software engineering, DevOps practices, and a deep understanding of the ML lifecycle, working to ensure seamless integration and operation of AI systems in a hybrid work environment.

Key Responsibilities

• Design, implement, and manage CI/CD pipelines for machine learning models.
• Develop and maintain infrastructure for model training, deployment, and monitoring.
• Automate ML workflows, including data validation, model training, and performance tracking.
• Collaborate with data scientists and software engineers to streamline the ML lifecycle.
• Ensure the scalability, reliability, and security of ML production systems.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Proven experience in MLOps, DevOps, or Site Reliability Engineering (SRE).
• Proficiency in cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Experience with scripting languages (e.g., Python, Bash) and infrastructure as code tools.
• Understanding of machine learning concepts and workflows.

Benefits

• Competitive salary and performance-driven bonuses.
• Hybrid work model offering a blend of office and remote flexibility.
• Comprehensive health insurance and retirement plans.
• Opportunities for continuous learning and skill development in MLOps and AI.
• A collaborative and innovative work culture in Kimberley .