Expert Cloud Infrastructure Designer

20 hours ago

Karachi, Sindh, Pakistan beBeeCloudArchitect Full time
Cloud Architect

Overview

We are seeking an experienced Cloud Architect to design and develop scalable, high-performance software architectures that leverage cloud-native technologies.

Key Responsibilities:

  • Lead the architectural design of software solutions, ensuring alignment with business requirements and technology strategy.
  • Design and develop scalable, high-performance 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 and select appropriate cloud services (e.g., AWS Sagemaker, Azure ML, Google AI Platform) to optimize performance, cost, and scalability.
  • Ensure the 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.

Qualifications and Skills:

  • Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related field.
  • Proven experience as a Cloud 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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