2-3 years of hands-on AI/ML development experience Solid Python programming skills Experience developing and deploying ML models on AWS Understanding of ML lifecycle from data preparation to deployment Exposure to SageMaker and AWS cloud services Experience with GenAI/LLM projects is highly preferred
Develop, train, evaluate, and deploy Machine Learning models for business use cases. Build predictive analytics, classification, regression, recommendation, and NLP solutions. Work with structured and unstructured datasets for model development. Perform feature engineering, model tuning, and performance optimization. Develop applications using LLMs and Generative AI technologies.
Build
Retrieval-Augmented Generation (RAG) pipelines. Integrate foundation models through AWS Bedrock or OpenAI APIs. Implement prompt engineering and LLM evaluation techniques.
Experience with AWS Bedrock and Foundation Models. Exposure to LangChain, RAG, and Vector Databases. Knowledge of MLOps practices and model monitoring. Familiarity with Docker and containerized deployments.
Certification in AWS Cloud or AWS Machine Learning is a plus.