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 effective, 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 .

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📌 Machine Learning Operations (MLOps) Engineer (British Columbia)
🏢 Placements24
📍 British Columbia