Machine Learning Operations Engineer

About the Role

Our client is a dynamic innovator in AI and Emerging Technologies , looking for a skilled Machine Learning Operations (MLOps) Engineer to join their team in Belfast . This role is crucial for bridging the gap between machine learning model development and production deployment, ensuring our AI systems are scalable, reliable, and efficient. You will be responsible for building and maintaining the infrastructure and workflows that support the end-to-end machine learning lifecycle. This is an excellent opportunity to work with cutting-edge technologies and play a key role in bringing advanced AI solutions to life.

Key Responsibilities

• Design, build, and maintain robust CI/CD pipelines for machine learning models .
• Implement and manage infrastructure for training, deployment, and monitoring of ML models in production.
• Automate ML workflows, including data ingestion, feature engineering, model training, and validation.
• Collaborate with data scientists and software engineers to ensure seamless integration of ML models.
• Monitor model performance in production and implement strategies for drift detection and retraining.
• Troubleshoot and resolve issues related to the ML infrastructure and deployed models.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• Proven experience in MLOps or DevOps, with a focus on machine learning systems.
• Strong understanding of machine learning principles and workflows.
• Proficiency in scripting languages (e.g., Python) and experience with CI/CD tools (e.g., Jenkins, GitLab CI).
• Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Familiarity with ML frameworks (e.g., TensorFlow, PyTorch) and MLOps tools (e.g., MLflow, Kubeflow).

Benefits

• Competitive salary and performance-related incentives.
• Comprehensive health and wellness benefits package.
• Opportunities for continuous learning and professional development in Belfast .
• Access to state-of-the-art technology and resources.
• Hybrid working model promoting work-life balance.