Cloud Native Architect

6 days ago

Karachi, Sindh, Pakistan beBee Careers Full time

Key Responsibilities

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- Design scalable, high-performance software architectures leveraging cloud-native technologies
- Lead architectural design of software solutions ensuring alignment with business requirements and technology strategy
- Design and develop scalable cloud architectures tailored for machine learning workloads including model training deployment and monitoring
- Collaborate with data scientists and ML engineers to understand model requirements and optimize training and inference workflows
- Evaluate select appropriate cloud services e.g. AWS Sagemaker Azure ML Google AI Platform to optimize performance cost and scalability
- Ensure security availability and integrity of cloud-based ML applications and data
- Conduct architectural reviews code reviews and provide technical leadership and guidance to development and data science teams
- Stay up-to-date with emerging cloud and ML technologies and industry trends to make informed architectural decisions
- Document architectural decisions designs and guidelines for implementation teams

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Qualifications and Skills

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- Bachelor's or Master's degree in Computer Science Software Engineering Data Science or a related field
- Proven experience as a Software Architect or Senior Developer with at least 10 years of technology expertise
- Strong knowledge of cloud platforms such as AWS Azure or Google Cloud including machine learning and data processing services
- Hands-on experience with cloud-based ML services e.g. AWS Sagemaker Azure Machine Learning Google AI Platform
- Proficiency in building ML pipelines using cloud-native architectures containerization e.g. Docker Kubernetes and serverless computing
- Solid programming skills in Python Java or other relevant languages used in ML development
- In-depth knowledge of software design patterns architectural principles and best practices
- Strong problem-solving skills with the ability to work in a fast-paced agile environment
- Excellent communication and leadership abilities to collaborate effectively with stakeholders data scientists and development teams
- Certifications in cloud technologies e.g. AWS Certified Solutions Architect Azure Solutions Architect Expert Google Cloud Architect
- Familiarity with data processing and storage solutions for ML workloads such as BigQuery Data Lake or Data Warehouse solutions
- Knowledge of security and compliance requirements for cloud-based ML applications
- Experience with version control and model tracking tools e.g. MLflow DVC

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