Join a dynamic banking and technology team as a Machine Learning Engineer. You'll work on cutting-edge projects that leverage machine learning to enhance banking solutions.
As a Machine Learning Engineer, you will be part of a forward-thinking team focused on integrating machine learning into banking solutions. Your role will involve designing and implementing ML pipelines that ensure efficient data processing and model deployment.
You will work closely with other engineers and data scientists to develop robust MLOps practices. This includes utilizing tools like Docker and Kubernetes for containerization and orchestration, as well as implementing CI/CD processes to streamline development workflows.
This position is ideal for someone with a strong background in machine learning and a passion for applying technology in the banking sector. You should be comfortable working in a fast-paced environment and be ready to tackle complex challenges.
Key responsibilities include: • Developing and maintaining ML pipelines • Collaborating with cross-functional teams • Implementing MLOps best practices • Utilizing Docker and Kubernetes for deployment • Ensuring CI/CD processes are in place
If you have a solid understanding of machine learning concepts and are eager to contribute to innovative banking solutions, this role could be a great fit for you.
You'll be taken to the original listing on PNet to apply.