Iris.ai

Machine Learning Engineer

• Work on research projects such as “Validation and improvement of context grounding metric”, “Knowledge Distillation for Efficient LLM Systems”, automatic prompt optimization, GraphRAG summarization, and evaluation of AI-generated summaries
• Analyze current metrics and propose improvements; implement upgraded Python implementations
• Conduct literature reviews, build experimental setups, and implement prototypes in Iris.ai’s codebase
• Benchmark and evaluate models and summarization methods; produce comparative analyses and evaluation reports
• Design, implement, and test frameworks for knowledge distillation and prompt optimization in RAG and Agentic AI systems
• Produce deliverables including Python implementations, prototypes, benchmarking results, and detailed reports
• Full-time commitment for 3-6 months, 40 hours per week; remote collaboration with Research Team
• Opportunity to carry out a Master Thesis project within the internship

Machine Learning Intern