Machine Learning Operations (MLOps) Engineer

About the Role

Our client is seeking a proactive Machine Learning Operations (MLOps) Engineer to join their cutting-edge AI team in Sheffield . This role is central to ensuring the seamless deployment, scaling, and management of machine learning models in production. You will bridge the gap between ML development and IT operations, implementing robust CI/CD pipelines, monitoring systems, and automation strategies. This is a fantastic opportunity for an engineer passionate about operationalizing AI to build reliable and efficient ML systems in a growth-focused company.

Key Responsibilities

• Develop and maintain CI/CD pipelines for machine learning models.
• Implement robust monitoring, logging, and alerting systems for ML models in production.
• Automate the training, testing, and deployment processes for ML models.
• Manage and optimize ML infrastructure on cloud platforms (e.g., AWS, Azure, GCP).
• Collaborate with data scientists and software engineers to ensure smooth model lifecycle management.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in DevOps, Site Reliability Engineering, or MLOps.
• Proficiency in scripting languages (e.g., Python, Bash) and infrastructure as code tools (e.g., Terraform, Ansible).
• Experience with containerization technologies (Docker, Kubernetes).
• Familiarity with machine learning concepts and workflows.

Benefits

• Competitive salary and performance bonuses.
• Comprehensive health and wellbeing benefits.
• Generous holiday allowance and flexible working hours.
• Opportunities for professional development and training.
• Collaborative team environment in Sheffield .