Data Scientist

What You'll Be Doing

• Support build end-to-end GenAI applications such as chatbots, voicebots, Talk-to-Data systems, where you will help buiild: data ingestion, retrieval layer, orchestration (e.g. LangChain/LlamaIndex/LangGraph), API/backend, and simple UI where needed.

• Implement RAG pipelines with vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks for relevance and robustness.

• Perform model selection, prompting strategies, and finetuning (LoRA/QLoRA/SFT) for text, code, and multimodal models, including guardrails, output evaluation and A/B testing.

• Integrating and optimizing LLMs interaction with external tools, APIs, and data sources in a standardized and scalable way by using Model Context Protocol (MCP) connectors

• Business understanding and translating problems into technical goals by defining tasks, auditing data feasibility, and highlighting issues.

• Supporting project delivery

What We’re Looking For

• Familiarity with theory behind various deep learning concepts

• Experience with Machine Learning (ML), especially in Generative AI (LLM/LMM) with focus on Natural Language Processing (NLP) or multimodal models.

• Fluency in Python and object programing, working knowledge of SQL and vector database

• Tech stack in Azure or GCP cloud

• Knowledge of specific Deep Learning and GenAI libraries like: NumPy, PyTorch, HuggingFace, LangChain, LangGraph and GenAI APIs i.e. OpenAI/Gemini.

• Experience with microservice architectures

• Experience with code repositories and code assistants

• Strong business acumen

• Ability to come up with creative solutions to address customer problem

• Nice to have:

• Experience in working with Databricks will be a plus

• Commercial experience proven by multiple successful projects in Generative AI, Natural Language Processing or Computer Vision will be a big plus