1. Bachelor’s degree in computer science or related field with a minimum 5 years of relevant experience.
  2. Experience in designing and implementing ML architecture on AWS using SageMaker with a minimum of 3 years.
  3. Must have experience in Banking IT.
  4. Must have technical experience in
    1. Amazon Web Services
    2. Hands-on experience in AWS SageMaker
    3. Serverless architecture concept understanding
    4. Execution of end-to-end ML pipeline and CI/CD implementation.
    5. Operationalizing and monitoring of models, beyond predictions concepts.
  5. Experience with CI/CD tools and practices like GitLab CI, Jenkins, or Bitbucket.
  6. Experience in Infrastructure-as-code (IaC) tools like Terraform and Ansible.
  7. Experience in version control tools like Git, GitHub, and MLFlow.
  8. Familiar with AWS services such as SageMaker, S3, EC2, IAM, VPC, Lambda, and ECS.
  9. Familiar with pipelining tools such as Step Functions, SageMaker Pipelines and Data Wrangler, serverless architecture.
  10. Experiences related to machine learning, deep learning, NLP, GNN, or distributed training.
  11. Experience defining system architectures and exploring technical feasibility trade-offs.
  12. Knowledge of model interpretability and explainability techniques.
  13. Experience optimizing for short term execution while planning for long term technical capabilities.
  14. Experience with productionizing, operationalizing, and monitoring machine learning models.
  15. Excellent collaboration skills and ability to work concisely when under pressure.
  16. Ability to think clearly, analyze quantitatively, problem-solver, scope technical requirements, and prioritize tasks.
  17. Certification in AWS Cloud is preferred.
  18. Strong verbal and written communication skills is a must.


Location

Bangalore North, India

Job Overview
Job Posted:
1 month ago
Job Expires:
Job Type
Full Time

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