Link Group
Senior Data Scientist – GenAI
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Data science
- Posted
Skills
Must have
- 6+ years of experience in Data Science, AI Engineering, Machine Learning, or a related field.
- 4+ years of professional Python development experience.
- 2+ years of hands-on experience with LLMs / Generative AI, preferably with RAG-based solutions.
- Strong knowledge of Python, LLMs, RAG, and Generative AI.
- Practical experience with LangChain, LlamaIndex, LangGraph, or similar frameworks.
- Experience with AI Agents / Agentic AI; MCP experience is a strong advantage.
- Knowledge of vector databases, hybrid search, reranking, and LLM evaluation.
- Experience with model fine-tuning, such as LoRA, QLoRA, or SFT.
- Experience with at least one major cloud platform: Azure, AWS, or GCP.
- Familiarity with Docker, Kubernetes, and CI/CD.
- Good understanding of AI/ML architectures and production deployment practices.
- Excellent English communication skills.
Nice to have
- Experience with Spark / Databricks.
- Experience with GitHub Actions, GitLab CI, or Azure DevOps.
- Experience with multi-agent systems and agentic AI workflows.
- Experience building scalable, production-grade AI systems.
- Experience with multimodal AI models.
Full description
##
We are looking for an experienced professional to join projects focused on Generative AI, LLMs, RAG, and AI Agents. The role combines AI Engineering, Data Science, and AI solution architecture, with a strong focus on building production-ready solutions.
Responsibilities
- Design and develop production-grade solutions using LLMs and Generative AI.
- Build and optimize RAG systems, including vector search, hybrid search, reranking, and query optimization.
- Develop AI Agents and agentic AI solutions.
- Work with frameworks such as LangChain, LlamaIndex, LangGraph, or similar technologies.
- Work with MCP to integrate AI agents with external tools and systems.
- Select appropriate models and develop prompt engineering and fine-tuning strategies, including LoRA/QLoRA/SFT.
- Implement LLM evaluation, validation, guardrails, and quality control mechanisms.
- Develop APIs/backend components and integrate AI solutions with existing systems.
- Contribute to technical architecture and technology selection.
- Collaborate with engineers, developers, and product teams.
- Share knowledge and support less experienced team members.
Requirements
- 6+ years of experience in Data Science, AI Engineering, Machine Learning, or a related field.
- 4+ years of professional Python development experience.
- 2+ years of hands-on experience with LLMs / Generative AI, preferably with RAG-based solutions.
- Strong knowledge of Python, LLMs, RAG, and Generative AI.
- Practical experience with LangChain, LlamaIndex, LangGraph, or similar frameworks.
- Experience with AI Agents / Agentic AI; MCP experience is a strong advantage.
- Knowledge of vector databases, hybrid search, reranking, and LLM evaluation.
- Experience with model fine-tuning, such as LoRA, QLoRA, or SFT.
- Experience with at least one major cloud platform: Azure, AWS, or GCP.
- Familiarity with Docker, Kubernetes, and CI/CD.
- Good understanding of AI/ML architectures and production deployment practices.
- Excellent English communication skills.
Nice to Have
- Experience with Spark / Databricks.
- Experience with GitHub Actions, GitLab CI, or Azure DevOps.