Offer summary
Qualifications:
Hands-on experience in Sagemaker and Amazon Bedrock, Knowledge of MLflow for data science code versioning.Key responsabilities:
- Handling Generative AI applications with Sagemaker
- DevSecOps Pipeline management
Match score not available
Priority access
Match score not available
AWS Sagemaker
74% Flex
Job description
Your missions
Skills
- Hands on Expert in Sagemaker & Sagemaker pipeline
- Hands on experience on handling Amazon Bedrock for Generative AI applications
- Excellent knowledge on MLflow for Data science code versioning tracking for model repository and integration knowledge with Sagemaker.
- Hands on experience in DevSecOps Pipeline(Jenkins, Bitbucket, Nexus)
- Experience with database systems including Postgres, MongoDB, DynamoDB
- Good knowledge of S3
- Should be Python development expert.
- Good knowledge of EMR serverless
- Good to have knowledge of IAM roles, Okta (Good to have)
- Concept of ECR, Docker , Open shift will be added advantage.
Required profile
Experience
Level of experience: Entry-level / graduate
Spoken language(s):
English
Check out the description to know which languages are mandatory. Share
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