About KnowDis:

KnowDis AI is a research-driven startup building cutting-edge solutions in Natural Language Processing (NLP) and Generative AI. Our AI tools are designed to automate and enhance business processes, including content generation, information retrieval, and document understanding. We work with clients across industries such as e-commerce, fashion, banking, and pharma, helping them unlock value through enterprise-ready AI solutions.

Role Overview:
We are hiring GenAI/LLM practitioners who are hands-on, curious, and execution-focused. Strong practical experience with LLM tools, prompt engineering, and real-world GenAI applications is essential.

Skills & Requirements :
Pytorch, LLM Finetuning, Frameworks - Langchain, LangGraph and other Generative AI frameworks
Bachelor's degree or equivalent in a quantative field from a Tier 1 Institute (Computer Science Engineering, Statistics, Mathematics, etc.)
The ideal candidates are rapid learners who understand both the capabilities and limitations of large language models, use them responsibly, and take full ownership of outcomes.





Key Responsibilities:
Design, test, and optimise LLM-driven solutions for real business use cases
Create, refine, and manage high-quality prompts, workflows, and agent setups
Rapidly prototype GenAI applications using existing tools, APIs, and platforms
Evaluate LLM outputs for accuracy, bias, safety, and reliability
Stay current with new LLM models, tools, and GenAI trends, and apply them pragmatically
Collaborate with business and technical teams to translate ideas into working AI solutions
Continuously improve the performance, efficiency, and cost-effectiveness of LLM usage

Selection Process:
Interested Candidates are mandatorily required to apply through this listing on Jigya. Only applications received through this posting will be evaluated further.
Shortlisted candidates may be required to appear in an Online Assessment and Screening interview administered by Jigya
Candidates se

📌 Data Scientist (India)
🏢 KnowDis AI
📍 India