Senior ML Operations Engineer
Core
Building and deploying predictive models to keep fraud and bad actors out of the banking system by enabling data scientists to move models from ideas to production.
Role type
Senior ML Operations Engineer
Builds
Scalable ML infrastructure, pipelines, and tools for model training, deployment, and monitoring in a cloud-native environment.
Domain
Financial services / Payments / Fraud detection
Deliverable
production ML models
Required skills
Python, AWS services, Docker, Kubernetes, CI/CD, MLflow, Kubeflow, distributed computing, software architecture, real-time model deployment
Preferred skills
Hybrid (OnPrem/Cloud) environments, Hadoop, Hive, Cloudera, Spark, Scala, Java
Technologies
AWS, Docker, Kubernetes, MLflow, Kubeflow, Spark, Hadoop, Hive, Cloudera
Responsibilities
Design and maintain scalable ML infrastructure and pipelines; optimize orchestration and resource usage; monitor model performance and detect drift; develop automation scripts for MLOps; collaborate with data scientists and engineers; provide technical mentorship and troubleshoot complex issues.
Seniority
Senior, hands-on IC
