As a Senior ML Platform Engineer, you will take ownership of designing, building, and maintaining the infrastructure that powers our Generative AI framework.
Requirements
- Design, build, and maintain scalable and secure ML infrastructure across development, testing, and production environments
- Automate and optimize the ML lifecycle
- Architect and manage the continuous integration and deployment pipelines and release processes using tools such as Kubeflow, MLflow, SageMaker, or custom Kubernetes solutions
- Implement monitoring systems for data drift, model performance, and infrastructure health
- Develop Tooling: Build and enhance ML engineering tooling for Model Development, Model Workbench, Model Training, Model Monitoring, and Model serving
- Work closely with data scientists and ML engineers to ensure reproducibility, scalability, and production-readiness of models
- Design and maintain pipelines for feature extraction, transformation, and storage using tools like Feature Store or custom solutions
- Ensure data quality, consistency, and lineage throughout the ML pipeline
- Ensure responsible use of data, model explainability, and auditability in line with organizational and legal standards
Benefits
- Dynamic, highly qualified, and diverse team
- Flat hierarchies and short decision-making processes
- Exciting and varying tasks for our product portfolio
- Excellent working environment, modern office space, and flexible working hours with the option of mobile working