We are seeking an experienced AWS Full Stack ML Engineer to build, deploy, and optimize large-scale financial modeling applications. This role focuses on MLOps, cloud infrastructure, and secure model deployment within AWS.
Qualifications
- Bachelor’s or Master’s degree in Computer Science or related quantitative field
- 4+ years of MLOps/DevOps experience supporting ML applications in production• Strong Python skills with ML frameworks (TensorFlow, PyTorch, Scikit-learn)
- Hands-on experience with AWS services such as SageMaker, Lambda, and Fargate
- Experience with Docker and container orchestration (ECS, Kubernetes, or EKS)
- CI/CD tools (GitLab, AWS CodePipeline, Jenkins)
- Workflow orchestration (Apache Airflow or AWS Step Functions)
Key Responsibilities
- Design and maintain end-to-end MLOps and CI/CD pipelines for model training and deployment
- Build scalable ETL and data pipelines for large financial datasets
- Provision and manage ML infrastructure using Terraform or CloudFormation
- Implement monitoring and logging to track model performance and system health
- Collaborate with cross-functional teams to deliver secure, production-ready ML solutions
