Role overview
We are seeking an AWS MLOps Engineer to design and support production-grade ML systems within a regulated financial services environment. This role focuses on building scalable MLOps pipelines, productionizing models, and managing secure AWS infrastructure for large-scale modeling applications.
What you'll work on
- Design and maintain end-to-end MLOps and CI/CD pipelines for training, deployment, and monitoring of ML models on AWS
- Productionize and integrate model and application code into scalable, reliable systems
- Build and manage ETL and data pipelines supporting large, complex financial datasets
- Implement secure, cost-efficient AWS infrastructure using IaC, monitoring, and cloud best practices
What we're looking for
- 6+ years of experience in MLOps, DevOps, or similar roles with hands-on ML deployment at scale
- Strong Python proficiency and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
- Deep experience with AWS services including SageMaker, S3, EC2, EKS/Fargate, Lambda, Glue, and IAM
- Experience with Docker, container orchestration (ECS/EKS), CI/CD tools, and strong software engineering fundamentals
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Machine Learning Mlops Pytorch Tensorflow Ai