Focus: Researching agentic AI capabilities and Small Language Models (SLMs), with emphasis on experimentation, modeling strategy, validation methods, and maturing approaches beyond proof of concept toward robust, reusable patterns.
Core Requirements:
- Strong background in applied machine learning / AI research
- Deep hands-on experience with GenAI systems and architectures
- Experience with Small Language Model (SLM) fine-tuning and adaptation
- Strong understanding of agentic AI concepts, including multi-step reasoning, tool use, orchestration, or workflow-based model behavior
- Strong grounding in classical machine learning as well as modern deep learning approaches
- Ability to design rigorous experiments and evaluate novel AI system behavior
- Strong communication skills and ability to engage with technical and non-technical stakeholders in English
Nice to Have:
- Understanding of scalable AI/ML system design and implementation realities
- Familiarity with deployment-oriented thinking for GenAI solutions
- Experience building or evaluating multi-component AI systems beyond single-model use cases
- Experience with reusable research patterns that can transition into practical application
- Exposure to model efficiency, optimization, or performance trade-offs