Generative AI Developer/ AI Engineer/Data Scientist

A Top IT MNC is hiring Generative AI Developer/ AI Engineer/ML Engineer/Data Scientists.

Work Mode: Remote

Experience: 7 years - 10 years

Only Immediate or Early Joiners !!

Mandatory Skills: AI Application Solution Design ,LLM Application Frameworks ,Python

REQUIREMENTS:

•Deep understanding of LLMs (e.g., GPTs, Llama, Claude, Gemini, Qwen, Mistral, BERT-family models) and their architectures (Transformers)

•Should have expert-level prompt engineering skills and proven experience implementing RAG patterns

•High proficiency in Python and standard AI/ML libraries (e.g., LangChain, LlamaIndex, LangGraph, LangSmith, Hugging Face Transformers, Scikit-learn, PyTorch/TensorFlow).

•Experience implementing RAG architectures and prompt engineering.

•Strong experience with fine-tuning and distillation techniques and evaluation.

•Strong experience using managed AI/ML services on the target cloud platform (e.g., Azure Machine Learning Studio, AI Foundry).

•Strong understanding of vector databases (e.g., Weaviate, Neo4j)

•understanding of GenAI evaluation metrics (e.g., BLEU, ROUGE, perplexity, semantic similarity, human evaluation).

•Architect and implement scalable GenAI and Agentic AI solutions end-to-end.

•Should be able to write high-quality, production-ready Python code with strong testing and maintainability practices.

•Should be able to productionize AI systems on Azure or AWS, ensuring enterprise-grade reliability and performance.

•Should be able to build and expose APIs using FastAPI, integrating with databases through an ORM.

RESPONSIBILITIES:

•Understanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.

•Mapping decisions with requirements and be able to translate the same to developers.

•Identifying different solutions and being able to narrow down the best option that meets the clients’ requirements.

•Defining guidelines and benchmarks for NFR considerations during project implementation.

•Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers.

•Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.

•Developing and designing the overall solution for defined functional and non-functional requirements;