of Git/GitHub workflows and DevOps tooling Nice to have: Experience with Docker or multi-container application architecture Familiarity with AI/ML technologies such as LLMs, NLP, LangGraph, PydanticAI, or AutoGen Experience with biological or scientific datasets (genomics, proteomics, etc.) Exposure to frontend development (React preferred) Experience benchmarking and improving AI/ML models or agent-based systems More ❯
data pipelines and AI workflows based on Azure cloud and Databricks. Apply Generative AI techniques for text, code, image, and multimodal use cases. Utilise agentic frameworks such as LangChain, LangGraph, MCP, Google ADK or similar Build solutions for LLM fine-tuning, RAG, and multi-agent AI workflows. Build Python based solutions using key data science and ML libraries (Pandas, NumPy More ❯
and Databricks ecosystems. Apply Generative AI techniques for text, code, image, and multi-modal use cases using advanced prompt engineering. Utilize modern GenAI toolkits and libraries, including: PyTorch LangChain, LangGraph, Model Context Protocol, Google's Agent Development Kit (ADK), and similar agentic frameworks. Develop experiments for LLM fine-tuning, retrieval-augmented generation (RAG), and multi-agent AI workflows . Deliver … expertise in: Python (advanced) AI/ML libraries (PyTorch, Hugging Face, Scikit-learn, TensorFlow, optional) Prompt engineering and fine-tuning LLMs for task-specific use cases Familiarity with LangChain, LangGraph, MCP, or other agentic frameworks for building AI applications. Excellent communication and stakeholder management skills. Strong ability to connect business concepts with AI-driven architectures and KPIs. More ❯
