Offer summary

Qualifications:

Strong experience with AWS CDK and CloudFormation for infrastructure as code (IAC)., Proficient in MLOps frameworks and concepts, including data preprocessing and model training., Experience with Docker, Kubernetes, and AWS SageMaker for model deployment and monitoring., Familiarity with CI/CD pipelines, MLflow, and Apache Airflow for workflow management..

Key responsabilities:

Manage and automate the deployment of machine learning models using AWS services.

Oversee data preprocessing and model training processes using AWS Glue and SageMaker Pipelines.

Implement model versioning and monitoring strategies to ensure model performance.

Collaborate with cross-functional teams to integrate MLOps practices into existing workflows.

Job description

Skills:
Docker, Kubernetes, AWS SageMaker, TensorFlow Extended (TFX), CI/CD pipelines, MLflow, Apache Airflow, Git,

The following are non-negotiable skill sets for MLOps.

Strong experience on AWS CDK as IAC.

Strong experience on AWS Cloudformation

Strong knowledge and experience on the MLOps frameworks and concepts

Strong Experience On

Data Preprocessing AWS Glue / S3 / Feature Store

Model Training SageMaker Pipelines

Model Versioning SageMaker Model Registry

Model Deployment SageMaker Inference / Lambda / EKS

Model Monitoring SageMaker Model Monitor + CloudWatch

Retraining & Automation AWS Step Functions / CodePipeline

Required profile