Senior Machine Learning Engineer for Cloud-Based Developer Platform
hace 4 semanas
We are seeking a highly motivated and detail-oriented Machine Learning (ML) Engineer to join our dynamic team at BASF. In this role, you will be responsible for developing and maintaining the ML components of our cloud-based developer platform, DevHub. You will work closely with our senior developers to create high-quality, scalable, and responsive AI solutions.
Responsibilities- 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 to extend the ML capabilities of the company to multiple teams, enabling reusability and standardization.
- Collaborate with the DevOps team to develop, run, and automate CI/CD pipelines specifically for ML models and workflows.
- Assist in monitoring cloud PaaS and IaaS components for availability, performance, and security as it pertains to ML models and services.
- Ensure adherence to BASF compliance and security guidelines in ML and AI development.
- Support and enable various AI, ML, and GenAI use cases on the DevHub Platform through effective model development and deployment.
- Contribute to the improvement of internal development processes, particularly those related to ML and AI.
- Proficiency in ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. Ability to design, implement, and manage machine learning models. Expertise in Python.
- Experience with Generative AI techniques and frameworks. Ability to develop and deploy GenAI models.
- Demonstrated experience with cloud platforms, particularly Azure. Ability to design, implement, and manage cloud infrastructure for ML and AI applications.
- Experience with Terraform for provisioning and managing infrastructure. Ability to write and maintain modular, reusable, and scalable Terraform code.
- Experience designing and implementing solutions to automate the experimentation and release cycle of machine learning, from traditional ML to LLM using CI/CD pipelines.
- Experience with data preprocessing, feature engineering, and data pipeline development.
- Experience with deploying, scaling, and managing ML models in Kubernetes environments.
- Proven experience working in Agile environments. Strong understanding of Agile principles and practices, including Scrum or Kanban. Ability to collaborate effectively with cross-functional teams.
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