Description

You will design and implement end-to-end AI/ML and Generative AI solutions, covering training, evaluation, optimization, and deployment on AWS.

This role is remote.

Responsibilities

• Develop scalable Python microservices using FastAPI or Flask for data pipelines and model inference.
• Architect RAG pipelines, embeddings, vector databases, and LLM-powered features like chatbots and semantic search.
• Build cloud-native applications on AWS using Lambda, ECS/Fargate, S3, API Gateway, DynamoDB, RDS/Aurora, SageMaker, and Bedrock.
• Implement CI/CD pipelines and Infrastructure-as-Code using Terraform or CloudFormation.
• Operationalize MLOps workflows including model versioning, containerized training, automated retraining, and performance monitoring.

Required Skills

• 5+ years of professional engineering experience.
• Strong hands-on experience in Python development for AI/ML and Generative AI solutions.
• Proven experience with AWS services for application and ML deployments, specifically Lambda, ECS/Fargate, S3, API Gateway, DynamoDB, RDS/Aurora, SageMaker, and Bedrock.
• Experience building APIs and microservices using FastAPI or Flask.
• Hands-on experience with RAG, embeddings, and vector databases.
• Experience with CI/CD and Infrastructure-as-Code tools such as Terraform or CloudFormation.
• Strong understanding of MLOps practices and production model monitoring.

Preferred Skills

• Experience with GitHub or GitLab for version control and CI/CD integration.

Key Skills

Education

Any Gradute