Senior AWS Full Stack Engineer

- Over 6 years of experience in MLOps, DevOps, or ML engineering - Demonstrated ability in designing and maintaining comprehensive MLOps pipelines - Proficient in CI/CD tools such as GitLab, Jenkins, and AWS CodePipeline - Familiar with workflow orchestration tools like AWS Step Functions or Apache Airflow - Strong skills in Python programming - Experienced with machine learning frameworks including TensorFlow, PyTorch, and Scikit-learn - Capable of refactoring and converting data science code for production use - Solid understanding of model performance monitoring and data drift detection - Extensive experience with AWS services such as Amazon SageMaker, S3, EC2, EKS/ECS/Fargate, Lambda, and AWS Glue - Familiarity with Infrastructure as Code leveraging Terraform or AWS CloudFormation - Strong knowledge of secure AWS architectures, including IAM roles and VPC configurations - Proven track record in optimizing AWS environments for performance and cost-effectiveness - Skilled in designing scalable ETL pipelines and managing data workflows - Ensuring data quality and availability for large-scale training and inference - Proficient in monitoring and alerting using tools like Amazon CloudWatch - Strong grasp of microservices architecture and system design principles - Comfortable with containerization (Docker) and orchestration (ECS/EKS) - Experienced with Git-based version control and code quality methodologies - Familiar with testing frameworks and debugging techniques - Excellent problem-solving skills and adept at troubleshooting - Ability to collaborate effectively with data scientists, engineers, and business stakeholders - Clear communicator who can simplify complex ML infrastructure topics into actionable solutions - Preferred: Experience in financial modeling environments or regulated sectors - AWS Certified in Machine Learning - Specialty and AWS Certified Solutions Architect - Associate - Additional relevant cloud or ML certifications considered - Bachelors degree in Computer Science, Information Systems, or related field.