Gen AI Architect

Role - Gen AI ArchitectYears of Experience - 8 to 10 yearsLocation - Bangalore, Noida, Pune, Mumbai, Hyderabad- Gen AI / LLM /Agentic AI - Gen AI - Experience in LLMs, Embedding Models, Prompt Engineering - Knowledge of statistical programming languages like Python - Good applied statistical skills - Good knowledge of machine learning algorithms - Proficiency in handling imperfections in data & generating insights and patterns. - Experience with Data Visualization Tools - Fine tuning of LLM - Evaluation Framework (RAGAS, ROUGE, BLUE Scrore) - Autoencoding model (Encoder: ROBERTA/ BERT/ DistilBERT) - Langsmith framework - Autoregressive model (Decoder: GPT/ BLOOM/ LLama/ Mistral/ Claude/ CodeGen/ OPT/ PaLM - RAG/Multimodal Architecture using Langchain/ LlamIndex - MCP Architecture - Experience Agentic AI Framework ( Crew AI, AutoGen, LangGraph, Google AVD etc. ) - Experience in Model deployment, LLMOps, Scalability and Performance - Fine tuning of LLM - AI ML exp. - Candidate has exp. in Transformer Architecture (Encoder and decoders) - Knowledge Graph implementation (If anyone has created knowledge graph, that's good) - Excellent Communication Skills - Strong Software Engineering Background (Productionizing the models) - Hands-on experience with data science tools - Problem-solving aptitude - Analytical mind and great business sense - Data mining or extracting usable data from valuable data sources. - Using machine learning tools to select features, create and optimize predictive models. - Carrying out preprocessing of structured and unstructured data - Enhancing data collection procedures to include all relevant information for developing analytic systems. - Processing, cleansing, and validating the integrity of data to be used for analysis. - Analyzing large amounts of information to find patterns and solutions. - Developing prediction systems and machine learning algorithms - Ability to use LLMs to build GenAI powered solutions. - Presenting results in a clear manner - Propose solutions and strategies to tackle business challenges. - Collaborate with Business and IT teams. - Designing and developing machine learning and deep learning systems - Knowledge of productionizing the ML and DL applications and monitoring

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