Python GEN AI

You are required to have 4-10 years of experience and expertise in AWS AI Services, AWS Bedrock, and Python AI. Your role will involve designing effective prompts and managing context to ensure accurate outputs from LLMs. This includes working on RAG Pipelines (Retrieval-Augmented Generation) and combining LLMs with external data sources using tools like vector databases (FAISS, Pinecone, Chroma). You will also be responsible for utilizing LLM Frameworks and tools such as LangChain, LlamaIndex, AutoGen, and LangGraph for building Gen AI apps. Additionally, your tasks will include fine-tuning models, evaluating performance, and implementing guardrails to prevent harmful or incorrect outputs. Qualifications required for this role include proficiency in Traditional AI/ML (Machine Learning & Deep Learning) with a strong understanding of classical machine learning algorithms like regression, classification, and clustering, along with solid statistics knowledge. Deep Learning skills involving neural networks such as CNN (Computer Vision), RNN / LSTM (Sequential data), and Transformers (modern NLP backbone) are also essential. Furthermore, you should have expertise in the model lifecycle encompassing training, validation, and deployment phases. Moreover, familiarity with MLOps engineering is crucial, where you will focus on deploying and managing models in production. This includes working on DevOps for ML, CI/CD pipelines, Docker & Kubernetes, and cloud infrastructure. Proficiency in MLOps tools like MLflow for experiment tracking, DVC for data versioning, Terraform for infra as code, and Jenkins for automation is required for this role. Please note that the company is scheduling face-to-face interviews on 21st May for the Bangalore location. For any further details or queries, you can contact HR at 9811293404. You are required to have 4-10 years of experience and expertise in AWS AI Services, AWS Bedrock, and Python AI. Your role will involve designing effective prompts and managing context to ensure accurate outputs from LLMs. This includes working on RAG Pipelines (Retrieval-Augmented Generation) and combining LLMs with external data sources using tools like vector databases (FAISS, Pinecone, Chroma). You will also be responsible for utilizing LLM Frameworks and tools such as LangChain, LlamaIndex, AutoGen, and LangGraph for building Gen AI apps. Additionally, your tasks will include fine-tuning models, evaluating performance, and implementing guardrails to prevent harmful or incorrect outputs. Qualifications required for this role include proficiency in Traditional AI/ML (Machine Learning & Deep Learning) with a strong understanding of classical machine learning algorithms like regression, classification, and clustering, along with solid statistics knowledge. Deep Learning skills involving neural networks such as CNN (Computer Vision), RNN / LSTM (Sequential data), and Transformers (modern NLP backbone) are also essential. Furthermore, you should have expertise in the model lifecycle encompassing training, validation, and deployment phases. Moreover, familiarity with MLOps engineering is crucial, where you will focus on deploying and managing models in production. This includes working on DevOps for ML, CI/CD pipelines, Docker & Kubernetes, and cloud infrastructure. Proficiency in MLOps tools like MLflow for experiment tracking, DVC for data versioning, Terraform for infra as code, and Jenkins for automation is required for this role. Please note that the company is scheduling face-to-face interviews on 21st May for the Bangalore location. For any further details or queries, you can contact HR at 9811293404.