Seeking a Machine Learning Engineer to build and scale machine learning infrastructure and workflows, supporting the development, training, deployment, and monitoring of thousands of machine learning models within an AWS-native environment.
Responsibilities
Develop, maintain, and scale machine learning pipelines for training, validation, and inference.
Build reusable components for model training, evaluation, deployment, and monitoring.
Translate notebooks and prototypes into production-grade training workflows.
Implement and maintain feature engineering workflows.
Collaborate with platform and DevOps teams for infrastructure management and automation.
Integrate model monitoring for performance metrics and alerting.
Improve retraining, rollback, and model versioning strategies.
Support experimentation infrastructure and A/B testing integrations.
Requirements
3+ years of experience in ML engineering.
Experience with AWS ML services.
Hands-on experience with Kubernetes.
Proficiency in Python and ML/DL libraries.
Experience with feature stores, data pipelines, and model versioning tools.
Familiarity with infrastructure-as-code and deployment tools.