Mode of Interview: Face to Face Inperson ( Walk in Interview)
Date of interview: 12th Sep 2026 (Saturday)
Roles and Responsibilities:
Design and implement GenAI solutions leveraging LLMs, RAG pipelines, and Agentic AI architectures.
Develop and fine-tune deep learning models for NLP tasks using frameworks like PyTorch or TensorFlow.
Build scalable APIs using FastAPI to serve AI models and integrate with enterprise systems.
Collaborate with data scientists and ML engineers to deploy models using CI/CD pipelines on Azure.
Optimize model performance and ensure robustness in production settings.
Stay updated with the latest research and advancements in generative AI and deep learning.
Scalability & Performance:Ability to write productive code and consider scalability and latency implications for Gen AI applications.
Containerization:Practical experience withDockerfor packaging and deploying applications
Key skills:
Solid programming skills inPythonwith experience in building ML/NLP applications.
Hands-on experience withDeep Learning,Machine Learning,
andNatural Language Processing.
Proficiency in working withLLMs(e.g., GPT,Gemini, LLaMA, Mistral) andRAGarchitecture.
Experience withAgentic AIframeworks and autonomous agent design.
Familiarity withFastAPIfor building RESTful APIs.
Experience withCI/CD pipelinesand deploying solutions onAzure Cloud, GCP and AWS
Solid understanding of data structures, algorithms, and software engineering principles.
Bachelors or masters degree in computer science, AI, Data Science, or related field.
Retrieval Augmented Generation (RAG):Hands-on experience in building and optimizing RAG pipelines from scratch
Expert-level proficiency and hands-on experience withLangChainand/orLlamaIndexfor building complex LLM applications, including chains, agents, memory, and tool integration.
Good to have skills:
Excellent Communication Skills
Robust Software Engineering Background (Productionizing the models)
Hands-on experience with data science tools
Problem-solving aptitude
Analytical mind and great business sense