Senior Data Scientist
150 - 180 PLN/ godz.B2B
SeniorFull-time·B2B
#427358·Dodano 2 dni temu·0
Źródło: nofluffjobs.comTech Stack / Keywords
PythonGenAILLMRAGLangChainLandGraph
Wymagania
- Minimum 6 years experience in Data Science / AI Engineering.
- At least 4 years of commercial experience coding in Python, including production-grade code.
- Minimum 2 years experience with production LLM-based solutions.
- Practical experience with RAG and building production pipelines.
- Strong knowledge of LLM, Generative AI, chatbots, and AI Agents.
- Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.
- Practical experience with MCP (Model Context Protocol) servers and clients.
- Knowledge of LLM evaluation, evaluators, validators, and guardrails.
- Good understanding of Machine Learning/AI, algorithms, model lifecycle, and AI solution architecture.
- Experience with cloud platforms; preferred Azure, acceptable AWS or GCP.
- Familiarity with CI/CD, testing, and containerization.
- Very good English language skills.
- Ability to work independently, analytical thinking, and complex problem solving.
- Ability to collaborate effectively with technical and business teams.
Obowiązki
- Designing GenAI solution architectures based on business and technical needs.
- Selecting appropriate LLM models and approaches including RAG, fine-tuning, agents, and prompt engineering.
- Building end-to-end GenAI applications encompassing data ingestion, retrieval, orchestration, backend, API, and user interfaces.
- Designing and developing advanced RAG pipelines involving vector databases, hybrid search, reranking, and query transformation.
- Working with frameworks such as LangChain, LangGraph, LlamaIndex or similar.
- Designing and developing AI Agents and agentic AI solutions.
- Implementing and using MCP (Model Context Protocol) on server and client sides.
- Selecting models, performing prompt engineering, and fine-tuning using techniques like LoRA, QLoRA, or SFT.
- Creating quality evaluation mechanisms for models and LLM applications, including evaluators, validators, A/B testing, and evaluation frameworks.
- Implementing guardrails, safety, PII handling, audit logs, and human-in-the-loop processes.
- Writing production-grade Python code with best practices for testing, packaging, and code quality.
- Collaborating with Data Engineers, Data Scientists, Software Engineers, and Product Owners.
- Participating in design of scalable architectures, enterprise integrations, and performance and SLA compliant solutions.
- Analyzing technical requirements, estimating work, and conducting discovery.
- Creating proofs of concept and experimenting with new GenAI solutions.
- Sharing knowledge and mentoring less experienced team members.
- Developing reusable components, libraries, and internal templates.
Benefity
- Sport subscription
- Private healthcare
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