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.MLOps Engineer Office based in Barcelona. This is what you will do: The MLOps Engineer reports to the IT Director of Insights and Analytics and is a critical role in Alexion IT RDU organization. You will be a key member of our IT team and play a crucial role in developing and implementing innovative machine learning solutions for our business. Your expertise in MLOps will be critical in designing, building, and deploying production-ready machine learning models at scale. You will be responsible for:
- Leading the development and implementation of MLOps infrastructure and tools for machine learning models
- Collaborating with cross-functional teams to identify, prioritize and solve business problems using machine learning techniques
- Designing, developing and implementing production-grade machine learning models that meet business requirements
- Overseeing the training, testing, and validation of machine learning models
- Ensuring that machine learning models meet high-quality… standards, including scalability, maintainability, and performance
- Design and implement efficient development environments and processes for ML applications.
- Communicating with stakeholders and senior management to provide updates on the progress of machine learning projects
- Developing assets, accelerators and thought capital for your practice by providing best in class framework and reusable components
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- Integrating Generative AI models based solutions within the broader machine learning ecosystem, ensuring they adhere to ethical guidelines and serve the intended business purposes
- Implementing robust monitoring and governance mechanisms for Generative AI models based solutions to ensure they evolve in alignment with business needs and regulatory standards You will need to have:
- Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field
- 4+ years of experience in developing and deploying machine learning models in production environments
- Hands-on experience building production models with focus on data science operations including serverless architectures, Kubernetes, Docker/containerization, and model upkeep and maintenance
- Familiarity with API-based application architecture and API frameworks.
- Experience with CICD orchestration frameworks, such as GitHub Actions, Jenkins or Bitbucket pipelines.
- Deep understanding of software development lifecycle and maintenance.
- Extensive experience with one or more orchestration tools (e.G Airflow, Flyte, Kubeflow)
- Experience working with MLOps tools like experiment tracking, model registry tools and feature stores (e
