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Machine Learning Operations Engineer
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Our clients in the Pharmaceutical Manufacturing industry are looking for a motivated Machine Learning Operations Engineer to join their UK team. As a Machine Learning Engineer, you will play a crucial role in taking AI models from scientific research to production, ensuring seamless integration and scalability. You’ll collaborate with data scientists, enhance the skillset of our existing team, and build robust infrastructure around the models. If you’re passionate about MLOps, data quality, and driving innovation, this role is for you Submit your CV and any additional required information after you have read this description by clicking on the application button. Responsibilities Include:
- Taking Models into Production: Collaborate with data scientists to deploy machine learning models into production environments.
- Implement MLOps practices to ensure its effectiveness and reliability to monitor model performance in real time.
- Skillset Enhancement: Elevate the skillset of our existing team by sharing best practices, conducting workshops, and fostering a culture of continuous learning.
- Infrastructure as Code (IaC) with Azure ML and Terraform: Leverage Azure Machine Learning services and Terraform to build scalable and reproducible ML infrastructure.
- Automate deployment, configuration, and management of ML resources.
- Interface Between Data Science and Model Building: Act as a bridge between data scientists and engineering teams. Translate research findings into practical solutions, ensuring alignment with business goals.
- 5+ years' experience as a Machine Learning Engineer
- Proven experience using Azure and Terraform to build, deploy, and manage high-quality ML models
- Must be well-versed in Infrastructure as Code (IaC)
- Experience implementing the core principles of ML Ops: Version control, automation, continuous X and model governance in aid to taking models into production
- Strong background in collaborating and communicating with cross functional teams
