Description

Design and implement end-to-end cloud machine learning solutions on AWS.

This role is on-site.

Responsibilities

• Design scalable predictive models for dynamic pricing, price promotion, and pricing strategy optimization.
• Build end-to-end solution architectures for model training, deployment, and retraining using native AWS services.
• Implement and manage MLOps principles and best practices for machine learning architecture.
• Execute A/B testing to evaluate the effectiveness of different pricing strategies.
• Develop and deploy real-time and batch inference processes and processing jobs.

Required Skills

• 8+ years of hands-on technical experience developing cloud ML solutions on AWS.
• Extensive experience using AWS SageMaker, including training jobs, real-time/batch inference, and processing jobs.
• Deep knowledge of supervised and unsupervised learning techniques, including clustering, decision trees, and artificial neural networks.
• Proficiency with workflow orchestration tools such as Airflow, Step Functions, SageMaker Pipelines, or Kubeflow.
• Experience implementing solutions using AWS Lambda.
• Proven ability to design software architecture and implement machine learning models.
• Any Graduate degree.

Key Skills

Education

Any Graduate