Senior AWS Python

Collaborate with Data Scientists and Platform Engineers to build scalable ML and data systems Develop and maintain high-performance, distributed data pipelines and machine learning infrastructure Convert machine learning models into production-ready services and APIs Automate model training, validation, deployment, and inferencing pipelines Design fault-tolerant, secure, and cost-effective cloud-native architectures using AWS services Implement Infrastructure as Code (IaC) using CloudFormation, Terraform, or AWS CDK Build CI/CD pipelines for deployment and testing automation Establish software engineering best practices including modularity, reusability, test coverage, and documentation Requirements:

5+ years of professional experience developing backend systems using Python Strong background in building and optimizing large-scale data pipelines and distributed systems Experience deploying machine learning models and managing ML workflows in production Solid understanding of software engineering principles including design patterns, version control, unit testing, and CI/CD Familiarity with object-oriented and functional programming practices Experience developing RESTful APIs and microservices Proven experience with cloud engineering on AWS, especially services like SageMaker, Glue, Lake Formation, and Athena Infrastructure as Code experience using CloudFormation, Terraform, or AWS CDK Experience with graph technologies and knowledge graphs (e.g., Neo4j, Amazon Neptune) is a plus Requirements:

5+ years of professional experience developing backend systems using Python Strong background in building and optimizing large-scale data pipelines and distributed systems Experience deploying machine learning models and managing ML workflows in production Solid understanding of software engineering principles including design patterns, version control, unit testing, and CI/CD Familiarity with object-oriented and functional programming practices Experience developing RESTful APIs and microservices Proven experience with cloud engineering on AWS, especially services like SageMaker, Glue, Lake Formation, and Athena Infrastructure as Code experience using CloudFormation, Terraform, or AWS CDK Experience with graph technologies and knowledge graphs (e.g., Neo4j, Amazon Neptune) is a plus Preferred Qualifications:

Prior experience working with machine learning operations (MLOps) or AI platform teams Knowledge of knowledge graph construction and semantic modeling Background in big data environments and real-time data processing frameworks Cloud Hybrid is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. Cloud Hybrid will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will Cloud Hybrid require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract

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