We are looking for a skilled and experienced Fullstack Data Scientist with solid expertise in Generative AI (GenAI) to lead projects focused on building and implementing advanced systems based on Large Language Models (LLMs), chatbots, AI agents, and Retrieval-Augmented Generation (RAG) mechanisms. As a Senior Data Scientist, you will be responsible for designing, implementing, and optimizing GenAI solutions, as well as mentoring teams. Your knowledge and experience will be crucial in making architectural decisions, selecting technologies, and implementing best practices in AI-driven development.
Tasks:
- Lead discovery and solution design for GenAI use cases, translating business problems into concrete architectures (LLM decision, RAGs, fine-tuning, agents, guardrails).
- Build end-to-end GenAI applications: 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 evaluation and A/B testing.
- Implement safety, compliance, and governance controls (input/output filters, PII handling, audit logs, human-in-the-loop review where required).
- Collaborate with data engineers, product owners, and full-stack developers on scalable architectures, SLAs, and integration with existing enterprise systems.
- Gather technical requirements and estimate planned work.
- Mentor other data scientists/engineers in GenAI patterns, code quality, and best practices; contribute to internal libraries, templates, and reusable components.
- Stay current with GenAI landscape (new open and hosted models, agentic frameworks, evaluation techniques) and perform targeted PoCs to validate them.
Requirements
Benefits
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