About the role
Responsibilities:
- System Architecture: Build, deploy, and manage scalable machine learning systems on AWS.
- Model Lifecycle: Manage the full ML lifecycle, including data preprocessing, feature engineering, and production-grade deployment.
- Generative AI: Develop solutions using modern frameworks like Amazon Bedrock and Hugging Face.
- Automation and MLOps: Implement MLOps best practices, including model monitoring and CI/CD for ML workflows.
- Collaboration: Work within agile environments alongside cross-functional data and engineering teams.
Requirements:
- AWS Core Services: Amazon SageMaker (Pipelines and Studio), Glue, Lambda, Step Functions, and EventBridge.
- Generative AI and NLP: Amazon Bedrock, Amazon Comprehend Medical, Amazon Textract, and Hugging Face Transformers.
- Deployment: API Gateway and containerised environments (ECS/EKS) for scalable inference.
- Programming: High proficiency in Python.
- Frameworks: TensorFlow, PyTorch, and Scikit-learn.
- Security: Familiarity with AWS IAM, KMS, CloudTrail, and general governance frameworks.