Description

You will build scalable, reliable, and cost-efficient ML pipelines and architect resilient cloud solutions.

Responsibilities

• Design and implement complex architectural solutions using AWS principles and industry standards.
• Build scalable ML pipelines using Python and AWS services (SageMaker, Lambda, Step Functions, S3, ECR).
• Lead technical design reviews, guiding teams on architectural best practices and creating design documentation.
• Determine code quality and test coverage, implementing tests to ensure high software quality.
• Mentor junior team members and actively participate in business requirement analysis with product teams.

Required Skills

• 8+ years of experience in engineering roles (technical lead, software engineer, architect).
• 5+ years using AWS to deploy scalable, secure cloud-native solutions.
• Hands-on design and development experience using Python, Flask, and Django.
• Deep understanding of cloud computing and AWS Well-Architected Framework.
• Strong experience with MLOps platforms like SageMaker, Kubeflow, or MLflow.
• Demonstrable familiarity with CI/CD processes (CodePipeline, Jenkins, etc.).
• Experience integrating with async messaging, logging, or queues (Kafka, SQS).
• Good understanding of distributed software applications, system integration, and APIs.
• Strong problem-solving and analytical skills with excellent documentation abilities.

Key Skills

Education

Any Graduate