Job Description:
We are seeking an applied Research Scientist to join our team.
In this role, you will lead the design development of large language models (LLMs)-based intelligent agent systems tailored fBoschs industrial manufacturing scenarios.
You will leverage LLMs, agent development frameworks, advanced NLP techniques to enable high-precision task automation, intelligent reasoning, decision support.
You will architect implement end-to-end agent capabilities—including function calling tool use, memory mechanisms, task planning, retrieval-augmented generation—to combine general AI capabilities with Boschs deep industrial knowledge.
A key part of this role is driving post-training fine-tuning efforts (e.g., instruction tuning, reward modeling, domain adaptation) that transform foundation models high-accuracy, production-ready agents freal-world factory use cases.
Beyond solution development, you will continuously scout evaluate the latest advancements in LLMs, agent frameworks, knowledge-enhanced AI to ensure our solutions remain state-of-the-art.
By integrating cutting-edge research with Boschs domain expertise, you will help close the "last mile" of AI deployment in industrial environments—delivering robust, reliable, high-precision agent performance in production-level applications.
Job Qualification:
? Design, develop, optimize LLM-powered agent systems—including memory, planning, reasoning capabilities—fhigh-precision task automation decision support in industrial manufacturing scenarios.
? Execute post-training alignment of LLMs—including supervised fine-tuning (instruction tuning, domain/task adaptation), parameter-efficient tuning methods (e.g., LoRA/QLoRA), reward modeling, preference optimization—to deliver controllable, high-accuracy behaviin industrial applications.
? Advance RAG systems beyond baseline implementations by optimizing retrieval, chunking, reranking, grounding to achieve high-accuracy, domain-adapted performance in industrial scenarios.
? Collaborate with domain experts to transform industrial data actionable insights using advanced NLP techniques
? Validate benchmark agent performance in production-like environments, ensuring robustness efficiency
? Contribute to scientific publications, patents, technical whitepapers as part of Boschs innovation initiatives
Basic Qualifications
? PhD Masters degree in Computer Science, Artificial Intelligence, NLP, related fields, with 3+ years of working experience in building real-world NLP agent systems
? Proficient in Python widely used LLM toolchains—covering model development (Transformers, PyTorch) agentchestration frameworks (LangChain, LangGraph, equivalent).
? Solid understanding of LLM post-training alignment workflows, including supervised fine-tuning (e.g., instruction tuning, domain adaptation) reward/preference model optimization, with hands-on experience in at least part of this pipeline.
? Solid understanding of agent architectures (e.g., RAG, memory, tool use, planning) their application in high-precision environments
? Proficiency in English ftechnical communication collaboration in interdisciplinary teams
? Understanding of the deployment challenges of LLM/AI systems in production environments
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Preferred Qualifications
? Experience applying LLM agents to industrial manufacturing domains
? Familiarity with knowledge graph related technologies- a plus
? Demonstrated contributions to top-tier AI/ML/NLP research (e.g., ACL, NeurIPS, ICML, ICLR)
? Some exposure to CV multimodal models is a plus
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