Senior Machine-Learning Engineer

hace 5 días

Madrid, España Basf A tiempo completo

.ABOUT US At BASF Digital Hub Madrid we develop innovative digital solutions for BASF, create new exciting customer experiences and business growth, and drive efficiencies in processes, helping to strengthen BASF's position as the digital leader in the chemical industry. We believe the right path is through creativity, trial and error and great people working and learning together. Become part of our team and develop the future with us - in a global team that embraces diversity and equal opportunities.JOIN THE TEAM DevHub is a cloud-based developer platform designed to streamline developers' work at BASF, providing essential tools and resources to ensure customer satisfaction. From infrastructure to developer tooling and security, the platform offers a feature-rich DevOps / MLOps experience.We are seeking a highly motivated and detail-oriented Machine Learning (ML) Engineer to join our dynamic team. In this role, you will be responsible for developing and maintaining the ML components. You will work closely with our senior developers to create high-quality, scalable, and responsive AI solutions.RESPONSIBILITIES Template Development: Design and build reusable ML templates and components to streamline the development of AI, ML, and Generative AI (GenAI) use cases.Develop the LLMOps framework: Make sure the ML capabilities of the company are extended to multiple teams, enabling reusability and standardization through an effective LLMOps framework.CI/CD Pipelines: Collaborate with the DevOps team to develop, run, and automate CI/CD pipelines specifically for ML models and workflows.Cloud Monitoring: Assist in monitoring cloud PaaS and IaaS components for availability, performance, and security as it pertains to ML models and services.Compliance and Security: Ensure adherence to BASF compliance and security guidelines in ML and AI development.Support and Enablement: Support and enable various AI, ML, and GenAI use cases on the DevHub Platform through effective model development and deployment.Process Improvement: Contribute to the improvement of internal development processes, particularly those related to ML and AI.QUALIFICATIONS Machine Learning Expertise: Proficiency in ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. Ability to design, implement, and manage machine learning models. Expertise in Python.Generative AI: Experience with Generative AI techniques and frameworks. Ability to develop and deploy GenAI models.Cloud Expertise: Demonstrated experience with cloud platforms, particularly Azure. Ability to design, implement, and manage cloud infrastructure for ML and AI applications.Infrastructure as Code (IaaC): Experience with Terraform for provisioning and managing infrastructure. Ability to write and maintain modular, reusable, and scalable Terraform code

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