MLOps Engineer | £500-£600 per day | Contract
We are seeking an experienced MLOps Engineer to enhance the deployment, monitoring, and management of machine learning models in production environments. This key role bridges the gap between data science and operations, ensuring the scalability, reliability, and efficiency of AI/ML workflows.
Key Responsibilities:
- Design, build, and maintain the infrastructure for automated ML model deployment, monitoring, and scaling.
- Collaborate closely with data scientists and software engineers to integrate ML models into live environments.
- Continuously monitor model performance, optimizing for scalability, reliability, and efficiency.
- Develop CI/CD pipelines for seamless model updates and deployments.
- Ensure robust model governance, versioning, and comprehensive documentation.
Qualifications and Skills:
- Bachelor’s degree in Computer Science, Data Science, or a related field.
- Proven experience with MLOps tools such as Kubernetes, Docker, and MLflow.
- Strong proficiency in cloud platforms (AWS, GCP, or Azure).
- In-depth understanding of CI/CD pipelines and DevOps practices.
- Familiarity with machine learning frameworks like TensorFlow and PyTorch.
Preferred Qualifications:
- Experience with model monitoring, A/B testing, and production deployments.
- Strong scripting skills in Python and Bash.
This is an exciting opportunity to contribute to cutting-edge AI/ML systems. Apply now and be part of an innovative team driving the future of machine learning operations!
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