Experienced AI/ML Engineer with expertise in Machine Learning, Deep Learning, NLP,and Generative AI. strong expertise in LLMs, Retrieval-Augmented Generation (RAG),Agentic AI, and MLOps to develop scalable and production-ready AI solutions.Key Responsibilities:Develop & Optimize AI/ML Solutions: Build and deploy LLMs, RAG, Agentic AI,and GenAI applications.ML Pipeline Development: Implement and automate scalable ML pipelines usingMLflow, AWS SageMaker, Databricks, and PySpark.MLOps Implementation: Establish CI/CD workflows, model versioning, monitoring,and automated retraining.Cloud &: Infrastructure: Leverage AWS AI/ML services (Sagemaker, Bedrock,Lambda, Step Functions, ECS/EKS) for scalable AI solutions.Data Engineering with PySpark: Optimize large-scale ETL workflows, data pipelines,and distributed data processing.LLMs & RAG Applications: Fine-tune and deploy LLMs integrated with vectordatabases (FAISS, Pinecone, ChromaDB).NLP & Deep Learning: Work with transformers, embeddings, multi-modal AImodels, and text processing frameworks. Orchestration & Containerization:Deploy and manage AI workloads using Kubernetes (EKS), Docker, and CI/CDpipelineSenior Data Engineer with special emphasis and experience of 10 to 15 yearson Artificial Intelligence and Machine Learning. Bachelor degree in computer scienceEngineering, or related field.Strong Hands on Experience on Python coding and all the python libraries. Manageand direct processes and R&D (research and development) to meet the needsof our AI strategy. Understand company and client challenges and how integrating AIcapabilities can help lead to solutions. As a Machine Learning Engineer, you will playa crucial role in the development and implementation of cutting-edge artificialintelligence products.No of Experience:10+ years' experience.
