Generative AI Architect

Description :

- 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)

Responsibility of / Expectations from the Role :

- 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