You will design and implement end-to-end AI/ML and Generative AI solutions using Python on AWS.
This role is on-site.
Responsibilities
Design and implement end-to-end AI/ML and Generative AI solutions, including model training, evaluation, optimization, and deployment.
Build and maintain cloud-native applications on AWS using Lambda, ECS/Fargate, S3, API Gateway, DynamoDB, RDS/Aurora, SageMaker, and Bedrock.
Develop high-performance Python microservices (FastAPI/Flask) to enable scalable data pipelines, model inference, and real-time analytics.
Architect and operationalize RAG pipelines, embeddings, vector databases, and LLM-powered automation for chatbots, summarization, semantic search, and anomaly detection.
Required Skills
5+ years of experience with Python and AI/ML development.
Strong proficiency in Generative AI (GenAI) concepts and implementation.
Hands-on experience with AWS services: Lambda, ECS/Fargate, S3, API Gateway, DynamoDB, RDS, SageMaker, and Bedrock.
Experience building microservices using FastAPI or Flask.
Proficiency in CI/CD tools such as GitHub, GitLab, or AWS CodePipeline.
Experience with Infrastructure-as-Code using Terraform or CloudFormation.
Bachelor's degree in Computer Science, Engineering, or a related field.
Preferred Skills
Experience building robust MLOps workflows, including model versioning, containerized training/inference, automated retraining, and monitoring.
Familiarity with vector databases and embedding techniques for RAG architectures.