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Mid-level ML role in Bangalore with broad AWS and ML requirements attracts many qualified applicants.
Machine learning and production AWS expertise is transferable across industries but requires specific ML experience.
Explicit 3-6 years requirement and mandatory AWS, Spark, LLM and production ML experience.
Build, train, and deploy complex machine learning models independently as end-to-end solutions.
Provision and manage AWS infrastructure components like VPC, EC2, EKS, EMR, S3, and RDS to support ML pipelines.
Design, maintain ML pipelines and contribute to system architecture and technical best practices.
Bachelor's or Master's degree in Engineering, Mathematics, Statistics, or related field.
3-6 years of professional experience in machine learning engineering.
Experience building and deploying ML models in production using Python, SQL, distributed computing frameworks (e.g., Spark).
Hands-on AWS experience managing ML workloads with VPC, EC2, EMR, RDS, S3, and EKS.
Experienced ML engineer capable of owning projects with autonomy and delivering scalable ML solutions.
Strong AWS infrastructure skills integrated with ML deployment and data processing workflows.
Familiar with modern AI/ML frameworks including LLMs or Generative AI, and orchestration tools like Airflow and MLflow.