Data Scientist (Generative AI)

• 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.

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

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

• Designing, 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 success metrics, auditing data feasibility, and aligning stakeholder expectations.

• Supporting project delivery.

• Supporting Pre-sales activities and initiatives.

• 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.

• Experience with business requirements gathering, transforming them into technical plan, data processing, feature engineering, models evaluation, hypothesis testing and model deployment.

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

• Strong tech stack in Azure or GCP cloud.

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

• Hands-on experience designing or operating MCP servers/clients for LLM agents.

• 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.

General:

• 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.

• Ability to lead juniors in project team.