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Machine Learning Operations (MLOps) Engineer
- norwich, norfolk, NR1 1AA, United Kingdom
- Permanent·Remote
- Full time
- £82,000 - £82,000 Per Annum
Job Description
About the Role
Our client is seeking an experienced Machine Learning Operations (MLOps) Engineer to join their globally distributed team on a fully remote basis. You will be responsible for streamlining and automating the machine learning lifecycle, from development and testing to deployment and monitoring. This role is critical for ensuring the reliability, scalability, and efficiency of our AI/ML systems in production. You will work closely with data scientists and software engineers to implement robust MLOps practices, enabling faster iteration and deployment of machine learning models in a seamless remote workflow.
Key Responsibilities
- Design, build, and maintain CI/CD pipelines for machine learning models.
- Implement and manage infrastructure for training, deployment, and monitoring of ML models.
- Develop automated testing and validation strategies for ML models and pipelines.
- Monitor model performance in production and implement retraining or rollback strategies as needed.
- Collaborate with data science and engineering teams to ensure smooth model deployment and integration.
- Contribute to the development of internal MLOps tools and best practices.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 4+ years of experience in software engineering or DevOps, with a focus on MLOps.
- Proficiency in scripting languages (e.g., Python, Bash) and containerization technologies (e.g., Docker, Kubernetes).
- Experience with cloud platforms (AWS, Azure, GCP) and their MLOps services.
- Familiarity with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and their deployment.
- Strong understanding of CI/CD principles and automation tools.
Benefits
- Highly competitive salary and bonus.
- Fully remote work arrangement with flexible hours.
- Comprehensive health, dental, and vision insurance.
- Generous allowance for home office setup and professional development.
- Opportunity to work on cutting-edge MLOps challenges and shape deployment strategies.
- A collaborative and supportive remote team environment.