About the job
ML Ops Engineer | Fintech | Scalable AI & Machine Learning
A leading embedded financing platform is looking for an ML Ops Engineer to build and maintain robust machine learning infrastructure in a fast-paced production environment. This role is crucial in bridging the gap between research and deployment, ensuring AI-driven credit risk solutions are seamlessly integrated and continuously optimised.
Key Responsibilities
1. Design, implement, and optimise scalable ML pipelines for training, validation, deployment, and monitoring.
2. Develop automation tools to streamline model updates and operational processes.
3. Implement performance monitoring and alerting systems to track model accuracy.
4. Collaborate with ML researchers and software engineers to integrate new models into production.
Required Skills and Experience
1. Proven experience in building and maintaining operational ML systems.
2. Strong Python coding skills with expertise in ML and data engineering libraries.
3. Experience with CI/CD, containerisation (Docker, Kubernetes), and version control (Git).
4. Strong problem-solving ability to identify and resolve issues in complex ML pipelines.
5. Familiarity with cloud infrastructure and data tools such as AWS, Terraform, Snowflake, and Jenkins.
6. Experience within financial services or lending environments.
This is an opportunity to join a forward-thinking organisation shaping the future of embedded finance.
#J-18808-Ljbffr