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