Software Architect

2 weeks ago

Lahore, Punjab, Pakistan beBeeCloud Full time $1,600,000 - $2,000,000

As a visionary Software Leader, you will design and develop cutting-edge software architectures that leverage cloud-native technologies to drive business innovation. You will lead the architectural design of software solutions, ensuring seamless alignment with business requirements and technology strategy.

Key Responsibilities

  • Design and develop cloud-optimized software 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 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 Senior Developer with at least 10 years of technology expertise.
  • Strong knowledge of cloud platforms, including machine learning and data processing services.
  • Hands-on experience with cloud-based ML services.
  • Proficiency in building ML pipelines using cloud-native architectures, containerization, 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.
  • Familiarity with data processing and storage solutions for ML workloads.
  • Knowledge of security and compliance requirements for cloud-based ML applications.
  • Experience with version control and model tracking tools.

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