Agentic AI R&D Intern

Bosch Group • Sunnyvale, CA

21h

About The Position

The Bosch Research and Technology Center North America (RTC-NA) is part of the global Bosch Group and conducts research and develops technologies for Bosch business fields. The Silicon Valley AI research organization focuses on Foundation Models and Generative AI, Human-AI Collaboration and Trustworthy AI, AI for ADAS and Autonomous Systems, AI Systems Engineering, and Industry AI. The Agentic AI Research Group conducts research in large language models, AI agents, and intelligent autonomous systems, including autonomous and multi-agent systems, reasoning and planning, memory, self-improvement, retrieval-augmented generation, reinforcement learning, and multimodal foundation models.

The intern will conduct Agentic AI research addressing real-world challenges in areas such as Industrial AI, Manufacturing, Mobility, and Smart Home. The role involves developing and validating novel AI technologies on real-world applications, working with Bosch researchers and domain experts in Silicon Valley and across the global research network, and contributing to AI systems for industrial deployment. Research findings may be published in leading AI conferences and journals.

Requirements

• Currently enrolled in a Ph.D. or Master's program in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, or a related field.
• Strong research background in Agentic AI, large language models, machine learning, natural language processing, or related areas.
• Experience developing AI agents using modern frameworks and ecosystems.
• Strong Python programming skills and experience with modern AI/ML frameworks.
• Familiarity with agent workflows involving tool use, function calling, retrieval, memory, and multi-step reasoning.
• Experience conducting independent research, designing experiments, and analyzing results.
• Strong written and verbal communication skills and ability to work effectively in a collaborative research environment.
• Minimum GPA of 3.0.

Nice To Haves

• Publication record in top-tier AI, NLP, or machine learning venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, AAAI, or COLM.
• Research experience in LLM-based agents, agent architecture, task planning, reasoning, and autonomous decision making.
• Research experience in agent optimization, including post-training, reinforcement learning, preference optimization, and self-improvement.
• Experience with RAG, agentic retrieval systems, and knowledge-grounded agents.
• Experience with multi-agent systems, agent collaboration, and distributed agent workflows.
• Experience with multimodal foundation models involving language, vision, and structured data.
• Experience in reinforcement learning, online learning, or adaptive decision-making systems.
• Experience with agent benchmarking, evaluation methodologies, reliability, safety, or alignment.
• Experience applying Agentic AI technologies to real-world domains such as engineering design or industrial automation.
• Open-source contributions or demonstrated leadership in AI research communities.

Responsibilities

• Conduct novel research in Agentic AI, LLMs, and related fields.
• Design, implement, and evaluate research prototypes demonstrating innovative AI agent capabilities.
• Collaborate with Bosch researchers and domain experts to address challenging industrial problems.
• Analyze experimental results and identify opportunities for scientific innovation.
• Publish research outcomes in top-tier AI conferences and journals.
• Contribute, depending on expertise and interests, to research topics including industrial agent systems; autonomous and multi-agent systems; agent reasoning, planning, and decision making; agent memory and long-horizon task execution; self-improvement, continual learning, and adaptation; tool use and agent-environment interaction; RAG and Agentic RAG; knowledge integration and grounding; LLM post-training, reinforcement learning, and test-time scaling; multimodal agents; human-agent collaboration; and agent evaluation, reliability, and safety.

What This Job Offers

• Career Level: Intern